xszheng2020/the_stack_dedup_python_hits_7 · Datasets at Hugging Face

557744044201420120afd01770e430d0ba065881

219,848

py

Python

boto3_type_annotations_with_docs/boto3_type_annotations/autoscaling/client.py

cowboygneox/boto3_type_annotations

450dce1de4e066b939de7eac2ec560ed1a7ddaa2

[ "MIT" ]

119

2018-12-01T18:20:57.000Z

2022-02-02T10:31:29.000Z

boto3_type_annotations_with_docs/boto3_type_annotations/autoscaling/client.py

cowboygneox/boto3_type_annotations

450dce1de4e066b939de7eac2ec560ed1a7ddaa2

[ "MIT" ]

15

2018-11-16T00:16:44.000Z

2021-11-13T03:44:18.000Z

boto3_type_annotations_with_docs/boto3_type_annotations/autoscaling/client.py

cowboygneox/boto3_type_annotations

450dce1de4e066b939de7eac2ec560ed1a7ddaa2

[ "MIT" ]

11

2019-05-06T05:26:51.000Z

2021-09-28T15:27:59.000Z

from typing import Optional from botocore.client import BaseClient from typing import Dict from botocore.paginate import Paginator from datetime import datetime from botocore.waiter import Waiter from typing import Union from typing import List class Client(BaseClient): def attach_instances(self, AutoScalingGroupName: str, InstanceIds: List = None): """ Attaches one or more EC2 instances to the specified Auto Scaling group. When you attach instances, Amazon EC2 Auto Scaling increases the desired capacity of the group by the number of instances being attached. If the number of instances being attached plus the desired capacity of the group exceeds the maximum size of the group, the operation fails. If there is a Classic Load Balancer attached to your Auto Scaling group, the instances are also registered with the load balancer. If there are target groups attached to your Auto Scaling group, the instances are also registered with the target groups. For more information, see `Attach EC2 Instances to Your Auto Scaling Group <https://docs.aws.amazon.com/autoscaling/ec2/userguide/attach-instance-asg.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/AttachInstances>`_ **Request Syntax** :: response = client.attach_instances( InstanceIds=[ 'string', ], AutoScalingGroupName='string' ) :type InstanceIds: list :param InstanceIds: The IDs of the instances. You can specify up to 20 instances. - *(string) --* :type AutoScalingGroupName: string :param AutoScalingGroupName: **[REQUIRED]** The name of the Auto Scaling group. :returns: None """ pass def attach_load_balancer_target_groups(self, AutoScalingGroupName: str, TargetGroupARNs: List) -> Dict: """ Attaches one or more target groups to the specified Auto Scaling group. To describe the target groups for an Auto Scaling group, use DescribeLoadBalancerTargetGroups . To detach the target group from the Auto Scaling group, use DetachLoadBalancerTargetGroups . With Application Load Balancers and Network Load Balancers, instances are registered as targets with a target group. With Classic Load Balancers, instances are registered with the load balancer. For more information, see `Attaching a Load Balancer to Your Auto Scaling Group <https://docs.aws.amazon.com/autoscaling/ec2/userguide/attach-load-balancer-asg.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/AttachLoadBalancerTargetGroups>`_ **Request Syntax** :: response = client.attach_load_balancer_target_groups( AutoScalingGroupName='string', TargetGroupARNs=[ 'string', ] ) **Response Syntax** :: {} **Response Structure** - *(dict) --* :type AutoScalingGroupName: string :param AutoScalingGroupName: **[REQUIRED]** The name of the Auto Scaling group. :type TargetGroupARNs: list :param TargetGroupARNs: **[REQUIRED]** The Amazon Resource Names (ARN) of the target groups. You can specify up to 10 target groups. - *(string) --* :rtype: dict :returns: """ pass def attach_load_balancers(self, AutoScalingGroupName: str, LoadBalancerNames: List) -> Dict: """ Attaches one or more Classic Load Balancers to the specified Auto Scaling group. To attach an Application Load Balancer or a Network Load Balancer instead, see AttachLoadBalancerTargetGroups . To describe the load balancers for an Auto Scaling group, use DescribeLoadBalancers . To detach the load balancer from the Auto Scaling group, use DetachLoadBalancers . For more information, see `Attaching a Load Balancer to Your Auto Scaling Group <https://docs.aws.amazon.com/autoscaling/ec2/userguide/attach-load-balancer-asg.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/AttachLoadBalancers>`_ **Request Syntax** :: response = client.attach_load_balancers( AutoScalingGroupName='string', LoadBalancerNames=[ 'string', ] ) **Response Syntax** :: {} **Response Structure** - *(dict) --* :type AutoScalingGroupName: string :param AutoScalingGroupName: **[REQUIRED]** The name of the Auto Scaling group. :type LoadBalancerNames: list :param LoadBalancerNames: **[REQUIRED]** The names of the load balancers. You can specify up to 10 load balancers. - *(string) --* :rtype: dict :returns: """ pass def batch_delete_scheduled_action(self, AutoScalingGroupName: str, ScheduledActionNames: List) -> Dict: """ Deletes one or more scheduled actions for the specified Auto Scaling group. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/BatchDeleteScheduledAction>`_ **Request Syntax** :: response = client.batch_delete_scheduled_action( AutoScalingGroupName='string', ScheduledActionNames=[ 'string', ] ) **Response Syntax** :: { 'FailedScheduledActions': [ { 'ScheduledActionName': 'string', 'ErrorCode': 'string', 'ErrorMessage': 'string' }, ] } **Response Structure** - *(dict) --* - **FailedScheduledActions** *(list) --* The names of the scheduled actions that could not be deleted, including an error message. - *(dict) --* Describes a scheduled action that could not be created, updated, or deleted. - **ScheduledActionName** *(string) --* The name of the scheduled action. - **ErrorCode** *(string) --* The error code. - **ErrorMessage** *(string) --* The error message accompanying the error code. :type AutoScalingGroupName: string :param AutoScalingGroupName: **[REQUIRED]** The name of the Auto Scaling group. :type ScheduledActionNames: list :param ScheduledActionNames: **[REQUIRED]** The names of the scheduled actions to delete. The maximum number allowed is 50. - *(string) --* :rtype: dict :returns: """ pass def batch_put_scheduled_update_group_action(self, AutoScalingGroupName: str, ScheduledUpdateGroupActions: List) -> Dict: """ Creates or updates one or more scheduled scaling actions for an Auto Scaling group. If you leave a parameter unspecified when updating a scheduled scaling action, the corresponding value remains unchanged. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/BatchPutScheduledUpdateGroupAction>`_ **Request Syntax** :: response = client.batch_put_scheduled_update_group_action( AutoScalingGroupName='string', ScheduledUpdateGroupActions=[ { 'ScheduledActionName': 'string', 'StartTime': datetime(2015, 1, 1), 'EndTime': datetime(2015, 1, 1), 'Recurrence': 'string', 'MinSize': 123, 'MaxSize': 123, 'DesiredCapacity': 123 }, ] ) **Response Syntax** :: { 'FailedScheduledUpdateGroupActions': [ { 'ScheduledActionName': 'string', 'ErrorCode': 'string', 'ErrorMessage': 'string' }, ] } **Response Structure** - *(dict) --* - **FailedScheduledUpdateGroupActions** *(list) --* The names of the scheduled actions that could not be created or updated, including an error message. - *(dict) --* Describes a scheduled action that could not be created, updated, or deleted. - **ScheduledActionName** *(string) --* The name of the scheduled action. - **ErrorCode** *(string) --* The error code. - **ErrorMessage** *(string) --* The error message accompanying the error code. :type AutoScalingGroupName: string :param AutoScalingGroupName: **[REQUIRED]** The name of the Auto Scaling group. :type ScheduledUpdateGroupActions: list :param ScheduledUpdateGroupActions: **[REQUIRED]** One or more scheduled actions. The maximum number allowed is 50. - *(dict) --* Describes one or more scheduled scaling action updates for a specified Auto Scaling group. Used in combination with BatchPutScheduledUpdateGroupAction . When updating a scheduled scaling action, all optional parameters are left unchanged if not specified. - **ScheduledActionName** *(string) --* **[REQUIRED]** The name of the scaling action. - **StartTime** *(datetime) --* The time for the action to start, in YYYY-MM-DDThh:mm:ssZ format in UTC/GMT only and in quotes (for example, ``\"2019-06-01T00:00:00Z\"`` ). If you specify ``Recurrence`` and ``StartTime`` , Amazon EC2 Auto Scaling performs the action at this time, and then performs the action based on the specified recurrence. If you try to schedule the action in the past, Amazon EC2 Auto Scaling returns an error message. - **EndTime** *(datetime) --* The time for the recurring schedule to end. Amazon EC2 Auto Scaling does not perform the action after this time. - **Recurrence** *(string) --* The recurring schedule for the action, in Unix cron syntax format. This format consists of five fields separated by white spaces: [Minute] [Hour] [Day_of_Month] [Month_of_Year] [Day_of_Week]. The value must be in quotes (for example, ``\"30 0 1 1,6,12 *\"`` ). For more information about this format, see `Crontab <http://crontab.org>`__ . - **MinSize** *(integer) --* The minimum size of the group. - **MaxSize** *(integer) --* The maximum size of the group. - **DesiredCapacity** *(integer) --* The number of EC2 instances that should be running in the group. :rtype: dict :returns: """ pass def can_paginate(self, operation_name: str = None): """ Check if an operation can be paginated. :type operation_name: string :param operation_name: The operation name. This is the same name as the method name on the client. For example, if the method name is ``create_foo``, and you\'d normally invoke the operation as ``client.create_foo(**kwargs)``, if the ``create_foo`` operation can be paginated, you can use the call ``client.get_paginator(\"create_foo\")``. :return: ``True`` if the operation can be paginated, ``False`` otherwise. """ pass def complete_lifecycle_action(self, LifecycleHookName: str, AutoScalingGroupName: str, LifecycleActionResult: str, LifecycleActionToken: str = None, InstanceId: str = None) -> Dict: """ Completes the lifecycle action for the specified token or instance with the specified result. This step is a part of the procedure for adding a lifecycle hook to an Auto Scaling group: * (Optional) Create a Lambda function and a rule that allows CloudWatch Events to invoke your Lambda function when Amazon EC2 Auto Scaling launches or terminates instances. * (Optional) Create a notification target and an IAM role. The target can be either an Amazon SQS queue or an Amazon SNS topic. The role allows Amazon EC2 Auto Scaling to publish lifecycle notifications to the target. * Create the lifecycle hook. Specify whether the hook is used when the instances launch or terminate. * If you need more time, record the lifecycle action heartbeat to keep the instance in a pending state. * **If you finish before the timeout period ends, complete the lifecycle action.** For more information, see `Amazon EC2 Auto Scaling Lifecycle Hooks <https://docs.aws.amazon.com/autoscaling/ec2/userguide/lifecycle-hooks.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/CompleteLifecycleAction>`_ **Request Syntax** :: response = client.complete_lifecycle_action( LifecycleHookName='string', AutoScalingGroupName='string', LifecycleActionToken='string', LifecycleActionResult='string', InstanceId='string' ) **Response Syntax** :: {} **Response Structure** - *(dict) --* :type LifecycleHookName: string :param LifecycleHookName: **[REQUIRED]** The name of the lifecycle hook. :type AutoScalingGroupName: string :param AutoScalingGroupName: **[REQUIRED]** The name of the Auto Scaling group. :type LifecycleActionToken: string :param LifecycleActionToken: A universally unique identifier (UUID) that identifies a specific lifecycle action associated with an instance. Amazon EC2 Auto Scaling sends this token to the notification target you specified when you created the lifecycle hook. :type LifecycleActionResult: string :param LifecycleActionResult: **[REQUIRED]** The action for the group to take. This parameter can be either ``CONTINUE`` or ``ABANDON`` . :type InstanceId: string :param InstanceId: The ID of the instance. :rtype: dict :returns: """ pass def create_auto_scaling_group(self, AutoScalingGroupName: str, MinSize: int, MaxSize: int, LaunchConfigurationName: str = None, LaunchTemplate: Dict = None, MixedInstancesPolicy: Dict = None, InstanceId: str = None, DesiredCapacity: int = None, DefaultCooldown: int = None, AvailabilityZones: List = None, LoadBalancerNames: List = None, TargetGroupARNs: List = None, HealthCheckType: str = None, HealthCheckGracePeriod: int = None, PlacementGroup: str = None, VPCZoneIdentifier: str = None, TerminationPolicies: List = None, NewInstancesProtectedFromScaleIn: bool = None, LifecycleHookSpecificationList: List = None, Tags: List = None, ServiceLinkedRoleARN: str = None): """ Creates an Auto Scaling group with the specified name and attributes. If you exceed your maximum limit of Auto Scaling groups, the call fails. For information about viewing this limit, see DescribeAccountLimits . For information about updating this limit, see `Amazon EC2 Auto Scaling Limits <https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-account-limits.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/CreateAutoScalingGroup>`_ **Request Syntax** :: response = client.create_auto_scaling_group( AutoScalingGroupName='string', LaunchConfigurationName='string', LaunchTemplate={ 'LaunchTemplateId': 'string', 'LaunchTemplateName': 'string', 'Version': 'string' }, MixedInstancesPolicy={ 'LaunchTemplate': { 'LaunchTemplateSpecification': { 'LaunchTemplateId': 'string', 'LaunchTemplateName': 'string', 'Version': 'string' }, 'Overrides': [ { 'InstanceType': 'string' }, ] }, 'InstancesDistribution': { 'OnDemandAllocationStrategy': 'string', 'OnDemandBaseCapacity': 123, 'OnDemandPercentageAboveBaseCapacity': 123, 'SpotAllocationStrategy': 'string', 'SpotInstancePools': 123, 'SpotMaxPrice': 'string' } }, InstanceId='string', MinSize=123, MaxSize=123, DesiredCapacity=123, DefaultCooldown=123, AvailabilityZones=[ 'string', ], LoadBalancerNames=[ 'string', ], TargetGroupARNs=[ 'string', ], HealthCheckType='string', HealthCheckGracePeriod=123, PlacementGroup='string', VPCZoneIdentifier='string', TerminationPolicies=[ 'string', ], NewInstancesProtectedFromScaleIn=True|False, LifecycleHookSpecificationList=[ { 'LifecycleHookName': 'string', 'LifecycleTransition': 'string', 'NotificationMetadata': 'string', 'HeartbeatTimeout': 123, 'DefaultResult': 'string', 'NotificationTargetARN': 'string', 'RoleARN': 'string' }, ], Tags=[ { 'ResourceId': 'string', 'ResourceType': 'string', 'Key': 'string', 'Value': 'string', 'PropagateAtLaunch': True|False }, ], ServiceLinkedRoleARN='string' ) :type AutoScalingGroupName: string :param AutoScalingGroupName: **[REQUIRED]** The name of the Auto Scaling group. This name must be unique within the scope of your AWS account. :type LaunchConfigurationName: string :param LaunchConfigurationName: The name of the launch configuration. This parameter, a launch template, a mixed instances policy, or an EC2 instance must be specified. For more information, see `Creating an Auto Scaling Group Using a Launch Configuration <https://docs.aws.amazon.com/autoscaling/ec2/userguide/create-asg.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . :type LaunchTemplate: dict :param LaunchTemplate: The launch template to use to launch instances. This parameter, a launch configuration, a mixed instances policy, or an EC2 instance must be specified. For more information, see `Creating an Auto Scaling Group Using a Launch Template <https://docs.aws.amazon.com/autoscaling/ec2/userguide/create-asg-launch-template.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . - **LaunchTemplateId** *(string) --* The ID of the launch template. You must specify either a template ID or a template name. - **LaunchTemplateName** *(string) --* The name of the launch template. You must specify either a template name or a template ID. - **Version** *(string) --* The version number, ``$Latest`` , or ``$Default`` . If the value is ``$Latest`` , Amazon EC2 Auto Scaling selects the latest version of the launch template when launching instances. If the value is ``$Default`` , Amazon EC2 Auto Scaling selects the default version of the launch template when launching instances. The default value is ``$Default`` . :type MixedInstancesPolicy: dict :param MixedInstancesPolicy: The mixed instances policy to use to launch instances. This parameter, a launch template, a launch configuration, or an EC2 instance must be specified. For more information, see `Auto Scaling Groups with Multiple Instance Types and Purchase Options <https://docs.aws.amazon.com/autoscaling/ec2/userguide/asg-purchase-options.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . - **LaunchTemplate** *(dict) --* The launch template and overrides. This parameter is required when creating an Auto Scaling group with a mixed instances policy, but is not required when updating the group. - **LaunchTemplateSpecification** *(dict) --* The launch template to use. You must specify either the launch template ID or launch template name in the request. - **LaunchTemplateId** *(string) --* The ID of the launch template. You must specify either a template ID or a template name. - **LaunchTemplateName** *(string) --* The name of the launch template. You must specify either a template name or a template ID. - **Version** *(string) --* The version number, ``$Latest`` , or ``$Default`` . If the value is ``$Latest`` , Amazon EC2 Auto Scaling selects the latest version of the launch template when launching instances. If the value is ``$Default`` , Amazon EC2 Auto Scaling selects the default version of the launch template when launching instances. The default value is ``$Default`` . - **Overrides** *(list) --* Any parameters that you specify override the same parameters in the launch template. Currently, the only supported override is instance type. You must specify between 2 and 20 overrides. - *(dict) --* Describes an override for a launch template. - **InstanceType** *(string) --* The instance type. For information about available instance types, see `Available Instance Types <https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/instance-types.html#AvailableInstanceTypes>`__ in the *Amazon Elastic Compute Cloud User Guide.* - **InstancesDistribution** *(dict) --* The instances distribution to use. If you leave this parameter unspecified when creating the group, the default values are used. - **OnDemandAllocationStrategy** *(string) --* Indicates how to allocate instance types to fulfill On-Demand capacity. The only valid value is ``prioritized`` , which is also the default value. This strategy uses the order of instance type overrides for the LaunchTemplate to define the launch priority of each instance type. The first instance type in the array is prioritized higher than the last. If all your On-Demand capacity cannot be fulfilled using your highest priority instance, then the Auto Scaling groups launches the remaining capacity using the second priority instance type, and so on. - **OnDemandBaseCapacity** *(integer) --* The minimum amount of the Auto Scaling group\'s capacity that must be fulfilled by On-Demand Instances. This base portion is provisioned first as your group scales. The default value is ``0`` . If you leave this parameter set to ``0`` , On-Demand Instances are launched as a percentage of the Auto Scaling group\'s desired capacity, per the ``OnDemandPercentageAboveBaseCapacity`` setting. - **OnDemandPercentageAboveBaseCapacity** *(integer) --* Controls the percentages of On-Demand Instances and Spot Instances for your additional capacity beyond ``OnDemandBaseCapacity`` . The range is 0–100. The default value is ``100`` . If you leave this parameter set to ``100`` , the percentages are 100% for On-Demand Instances and 0% for Spot Instances. - **SpotAllocationStrategy** *(string) --* Indicates how to allocate Spot capacity across Spot pools. The only valid value is ``lowest-price`` , which is also the default value. The Auto Scaling group selects the cheapest Spot pools and evenly allocates your Spot capacity across the number of Spot pools that you specify. - **SpotInstancePools** *(integer) --* The number of Spot pools to use to allocate your Spot capacity. The Spot pools are determined from the different instance types in the Overrides array of LaunchTemplate . The range is 1–20 and the default is 2. - **SpotMaxPrice** *(string) --* The maximum price per unit hour that you are willing to pay for a Spot Instance. If you leave the value of this parameter blank (which is the default), the maximum Spot price is set at the On-Demand price. To remove a value that you previously set, include the parameter but leave the value blank. :type InstanceId: string :param InstanceId: The ID of the instance used to create a launch configuration for the group. This parameter, a launch configuration, a launch template, or a mixed instances policy must be specified. When you specify an ID of an instance, Amazon EC2 Auto Scaling creates a new launch configuration and associates it with the group. This launch configuration derives its attributes from the specified instance, except for the block device mapping. For more information, see `Create an Auto Scaling Group Using an EC2 Instance <https://docs.aws.amazon.com/autoscaling/ec2/userguide/create-asg-from-instance.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . :type MinSize: integer :param MinSize: **[REQUIRED]** The minimum size of the group. :type MaxSize: integer :param MaxSize: **[REQUIRED]** The maximum size of the group. :type DesiredCapacity: integer :param DesiredCapacity: The number of EC2 instances that should be running in the group. This number must be greater than or equal to the minimum size of the group and less than or equal to the maximum size of the group. If you do not specify a desired capacity, the default is the minimum size of the group. :type DefaultCooldown: integer :param DefaultCooldown: The amount of time, in seconds, after a scaling activity completes before another scaling activity can start. The default value is ``300`` . For more information, see `Scaling Cooldowns <https://docs.aws.amazon.com/autoscaling/ec2/userguide/Cooldown.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . :type AvailabilityZones: list :param AvailabilityZones: One or more Availability Zones for the group. This parameter is optional if you specify one or more subnets for ``VPCZoneIdentifier`` . Conditional: If your account supports EC2-Classic and VPC, this parameter is required to launch instances into EC2-Classic. - *(string) --* :type LoadBalancerNames: list :param LoadBalancerNames: One or more Classic Load Balancers. To specify an Application Load Balancer or a Network Load Balancer, use ``TargetGroupARNs`` instead. For more information, see `Using a Load Balancer With an Auto Scaling Group <https://docs.aws.amazon.com/autoscaling/ec2/userguide/autoscaling-load-balancer.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . - *(string) --* :type TargetGroupARNs: list :param TargetGroupARNs: The Amazon Resource Names (ARN) of the target groups. - *(string) --* :type HealthCheckType: string :param HealthCheckType: The service to use for the health checks. The valid values are ``EC2`` and ``ELB`` . The default value is ``EC2`` . If you configure an Auto Scaling group to use ELB health checks, it considers the instance unhealthy if it fails either the EC2 status checks or the load balancer health checks. For more information, see `Health Checks for Auto Scaling Instances <https://docs.aws.amazon.com/autoscaling/ec2/userguide/healthcheck.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . :type HealthCheckGracePeriod: integer :param HealthCheckGracePeriod: The amount of time, in seconds, that Amazon EC2 Auto Scaling waits before checking the health status of an EC2 instance that has come into service. During this time, any health check failures for the instance are ignored. The default value is ``0`` . For more information, see `Health Checks for Auto Scaling Instances <https://docs.aws.amazon.com/autoscaling/ec2/userguide/healthcheck.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . Conditional: This parameter is required if you are adding an ``ELB`` health check. :type PlacementGroup: string :param PlacementGroup: The name of the placement group into which to launch your instances, if any. A placement group is a logical grouping of instances within a single Availability Zone. You cannot specify multiple Availability Zones and a placement group. For more information, see `Placement Groups <https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/placement-groups.html>`__ in the *Amazon EC2 User Guide for Linux Instances* . :type VPCZoneIdentifier: string :param VPCZoneIdentifier: A comma-separated list of subnet IDs for your virtual private cloud (VPC). If you specify ``VPCZoneIdentifier`` with ``AvailabilityZones`` , the subnets that you specify for this parameter must reside in those Availability Zones. Conditional: If your account supports EC2-Classic and VPC, this parameter is required to launch instances into a VPC. :type TerminationPolicies: list :param TerminationPolicies: One or more termination policies used to select the instance to terminate. These policies are executed in the order that they are listed. For more information, see `Controlling Which Instances Auto Scaling Terminates During Scale In <https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-instance-termination.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . - *(string) --* :type NewInstancesProtectedFromScaleIn: boolean :param NewInstancesProtectedFromScaleIn: Indicates whether newly launched instances are protected from termination by Amazon EC2 Auto Scaling when scaling in. For more information about preventing instances from terminating on scale in, see `Instance Protection <https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-instance-termination.html#instance-protection>`__ in the *Amazon EC2 Auto Scaling User Guide* . :type LifecycleHookSpecificationList: list :param LifecycleHookSpecificationList: One or more lifecycle hooks. - *(dict) --* Describes a lifecycle hook. Used in combination with CreateAutoScalingGroup . A lifecycle hook tells Amazon EC2 Auto Scaling to perform an action on an instance when the instance launches (before it is put into service) or as the instance terminates (before it is fully terminated). This step is a part of the procedure for creating a lifecycle hook for an Auto Scaling group: * (Optional) Create a Lambda function and a rule that allows CloudWatch Events to invoke your Lambda function when Amazon EC2 Auto Scaling launches or terminates instances. * (Optional) Create a notification target and an IAM role. The target can be either an Amazon SQS queue or an Amazon SNS topic. The role allows Amazon EC2 Auto Scaling to publish lifecycle notifications to the target. * **Create the lifecycle hook. Specify whether the hook is used when the instances launch or terminate.** * If you need more time, record the lifecycle action heartbeat to keep the instance in a pending state using using RecordLifecycleActionHeartbeat . * If you finish before the timeout period ends, complete the lifecycle action using CompleteLifecycleAction . For more information, see `Amazon EC2 Auto Scaling Lifecycle Hooks <https://docs.aws.amazon.com/autoscaling/ec2/userguide/lifecycle-hooks.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . You can view the lifecycle hooks for an Auto Scaling group using DescribeLifecycleHooks . You can modify an existing lifecycle hook or create new lifecycle hooks using PutLifecycleHook . If you are no longer using a lifecycle hook, you can delete it using DeleteLifecycleHook . - **LifecycleHookName** *(string) --* **[REQUIRED]** The name of the lifecycle hook. - **LifecycleTransition** *(string) --* **[REQUIRED]** The state of the EC2 instance to which you want to attach the lifecycle hook. The valid values are: * autoscaling:EC2_INSTANCE_LAUNCHING * autoscaling:EC2_INSTANCE_TERMINATING - **NotificationMetadata** *(string) --* Additional information that you want to include any time Amazon EC2 Auto Scaling sends a message to the notification target. - **HeartbeatTimeout** *(integer) --* The maximum time, in seconds, that can elapse before the lifecycle hook times out. If the lifecycle hook times out, Amazon EC2 Auto Scaling performs the action that you specified in the ``DefaultResult`` parameter. You can prevent the lifecycle hook from timing out by calling RecordLifecycleActionHeartbeat . - **DefaultResult** *(string) --* Defines the action the Auto Scaling group should take when the lifecycle hook timeout elapses or if an unexpected failure occurs. The valid values are ``CONTINUE`` and ``ABANDON`` . The default value is ``ABANDON`` . - **NotificationTargetARN** *(string) --* The ARN of the target that Amazon EC2 Auto Scaling sends notifications to when an instance is in the transition state for the lifecycle hook. The notification target can be either an SQS queue or an SNS topic. - **RoleARN** *(string) --* The ARN of the IAM role that allows the Auto Scaling group to publish to the specified notification target, for example, an Amazon SNS topic or an Amazon SQS queue. :type Tags: list :param Tags: One or more tags. For more information, see `Tagging Auto Scaling Groups and Instances <https://docs.aws.amazon.com/autoscaling/ec2/userguide/autoscaling-tagging.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . - *(dict) --* Describes a tag for an Auto Scaling group. - **ResourceId** *(string) --* The name of the group. - **ResourceType** *(string) --* The type of resource. The only supported value is ``auto-scaling-group`` . - **Key** *(string) --* **[REQUIRED]** The tag key. - **Value** *(string) --* The tag value. - **PropagateAtLaunch** *(boolean) --* Determines whether the tag is added to new instances as they are launched in the group. :type ServiceLinkedRoleARN: string :param ServiceLinkedRoleARN: The Amazon Resource Name (ARN) of the service-linked role that the Auto Scaling group uses to call other AWS services on your behalf. By default, Amazon EC2 Auto Scaling uses a service-linked role named AWSServiceRoleForAutoScaling, which it creates if it does not exist. For more information, see `Service-Linked Roles <https://docs.aws.amazon.com/autoscaling/ec2/userguide/autoscaling-service-linked-role.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . :returns: None """ pass def create_launch_configuration(self, LaunchConfigurationName: str, ImageId: str = None, KeyName: str = None, SecurityGroups: List = None, ClassicLinkVPCId: str = None, ClassicLinkVPCSecurityGroups: List = None, UserData: str = None, InstanceId: str = None, InstanceType: str = None, KernelId: str = None, RamdiskId: str = None, BlockDeviceMappings: List = None, InstanceMonitoring: Dict = None, SpotPrice: str = None, IamInstanceProfile: str = None, EbsOptimized: bool = None, AssociatePublicIpAddress: bool = None, PlacementTenancy: str = None): """ Creates a launch configuration. If you exceed your maximum limit of launch configurations, the call fails. For information about viewing this limit, see DescribeAccountLimits . For information about updating this limit, see `Amazon EC2 Auto Scaling Limits <https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-account-limits.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . For more information, see `Launch Configurations <https://docs.aws.amazon.com/autoscaling/ec2/userguide/LaunchConfiguration.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/CreateLaunchConfiguration>`_ **Request Syntax** :: response = client.create_launch_configuration( LaunchConfigurationName='string', ImageId='string', KeyName='string', SecurityGroups=[ 'string', ], ClassicLinkVPCId='string', ClassicLinkVPCSecurityGroups=[ 'string', ], UserData='string', InstanceId='string', InstanceType='string', KernelId='string', RamdiskId='string', BlockDeviceMappings=[ { 'VirtualName': 'string', 'DeviceName': 'string', 'Ebs': { 'SnapshotId': 'string', 'VolumeSize': 123, 'VolumeType': 'string', 'DeleteOnTermination': True|False, 'Iops': 123, 'Encrypted': True|False }, 'NoDevice': True|False }, ], InstanceMonitoring={ 'Enabled': True|False }, SpotPrice='string', IamInstanceProfile='string', EbsOptimized=True|False, AssociatePublicIpAddress=True|False, PlacementTenancy='string' ) :type LaunchConfigurationName: string :param LaunchConfigurationName: **[REQUIRED]** The name of the launch configuration. This name must be unique within the scope of your AWS account. :type ImageId: string :param ImageId: The ID of the Amazon Machine Image (AMI) to use to launch your EC2 instances. If you do not specify ``InstanceId`` , you must specify ``ImageId`` . For more information, see `Finding an AMI <https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/finding-an-ami.html>`__ in the *Amazon EC2 User Guide for Linux Instances* . :type KeyName: string :param KeyName: The name of the key pair. For more information, see `Amazon EC2 Key Pairs <https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ec2-key-pairs.html>`__ in the *Amazon EC2 User Guide for Linux Instances* . :type SecurityGroups: list :param SecurityGroups: One or more security groups with which to associate the instances. If your instances are launched in EC2-Classic, you can either specify security group names or the security group IDs. For more information, see `Amazon EC2 Security Groups <https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/using-network-security.html>`__ in the *Amazon EC2 User Guide for Linux Instances* . If your instances are launched into a VPC, specify security group IDs. For more information, see `Security Groups for Your VPC <https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_SecurityGroups.html>`__ in the *Amazon Virtual Private Cloud User Guide* . - *(string) --* :type ClassicLinkVPCId: string :param ClassicLinkVPCId: The ID of a ClassicLink-enabled VPC to link your EC2-Classic instances to. This parameter is supported only if you are launching EC2-Classic instances. For more information, see `ClassicLink <https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/vpc-classiclink.html>`__ in the *Amazon EC2 User Guide for Linux Instances* and `Linking EC2-Classic Instances to a VPC <https://docs.aws.amazon.com/autoscaling/ec2/userguide/asg-in-vpc.html#as-ClassicLink>`__ in the *Amazon EC2 Auto Scaling User Guide* . :type ClassicLinkVPCSecurityGroups: list :param ClassicLinkVPCSecurityGroups: The IDs of one or more security groups for the specified ClassicLink-enabled VPC. For more information, see `ClassicLink <https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/vpc-classiclink.html>`__ in the *Amazon EC2 User Guide for Linux Instances* and `Linking EC2-Classic Instances to a VPC <https://docs.aws.amazon.com/autoscaling/ec2/userguide/asg-in-vpc.html#as-ClassicLink>`__ in the *Amazon EC2 Auto Scaling User Guide* . Conditional: This parameter is required if you specify a ClassicLink-enabled VPC, and is not supported otherwise. - *(string) --* :type UserData: string :param UserData: The user data to make available to the launched EC2 instances. For more information, see `Instance Metadata and User Data <https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ec2-instance-metadata.html>`__ in the *Amazon EC2 User Guide for Linux Instances* . **This value will be base64 encoded automatically. Do not base64 encode this value prior to performing the operation.** :type InstanceId: string :param InstanceId: The ID of the instance to use to create the launch configuration. The new launch configuration derives attributes from the instance, except for the block device mapping. If you do not specify ``InstanceId`` , you must specify both ``ImageId`` and ``InstanceType`` . To create a launch configuration with a block device mapping or override any other instance attributes, specify them as part of the same request. For more information, see `Create a Launch Configuration Using an EC2 Instance <https://docs.aws.amazon.com/autoscaling/ec2/userguide/create-lc-with-instanceID.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . :type InstanceType: string :param InstanceType: The instance type of the EC2 instance. If you do not specify ``InstanceId`` , you must specify ``InstanceType`` . For information about available instance types, see `Available Instance Types <https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/instance-types.html#AvailableInstanceTypes>`__ in the *Amazon EC2 User Guide for Linux Instances.* :type KernelId: string :param KernelId: The ID of the kernel associated with the AMI. :type RamdiskId: string :param RamdiskId: The ID of the RAM disk associated with the AMI. :type BlockDeviceMappings: list :param BlockDeviceMappings: One or more mappings that specify how block devices are exposed to the instance. For more information, see `Block Device Mapping <https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/block-device-mapping-concepts.html>`__ in the *Amazon EC2 User Guide for Linux Instances* . - *(dict) --* Describes a block device mapping. - **VirtualName** *(string) --* The name of the virtual device (for example, ``ephemeral0`` ). - **DeviceName** *(string) --* **[REQUIRED]** The device name exposed to the EC2 instance (for example, ``/dev/sdh`` or ``xvdh`` ). For more information, see `Device Naming on Linux Instances <https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/device_naming.html>`__ in the *Amazon EC2 User Guide for Linux Instances* . - **Ebs** *(dict) --* The information about the Amazon EBS volume. - **SnapshotId** *(string) --* The ID of the snapshot. This parameter is optional if you specify a volume size. - **VolumeSize** *(integer) --* The volume size, in GiB. Constraints: 1-1,024 for ``standard`` , 4-16,384 for ``io1`` , 1-16,384 for ``gp2`` , and 500-16,384 for ``st1`` and ``sc1`` . If you specify a snapshot, the volume size must be equal to or larger than the snapshot size. Default: If you create a volume from a snapshot and you don\'t specify a volume size, the default is the snapshot size. .. note:: At least one of VolumeSize or SnapshotId is required. - **VolumeType** *(string) --* The volume type, which can be ``standard`` for Magnetic, ``io1`` for Provisioned IOPS SSD, ``gp2`` for General Purpose SSD, ``st1`` for Throughput Optimized HDD, or ``sc1`` for Cold HDD. For more information, see `Amazon EBS Volume Types <https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/EBSVolumeTypes.html>`__ in the *Amazon EC2 User Guide for Linux Instances* . Valid values: ``standard`` | ``io1`` | ``gp2`` | ``st1`` | ``sc1`` - **DeleteOnTermination** *(boolean) --* Indicates whether the volume is deleted on instance termination. The default value is ``true`` . - **Iops** *(integer) --* The number of I/O operations per second (IOPS) to provision for the volume. For more information, see `Amazon EBS Volume Types <https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/EBSVolumeTypes.html>`__ in the *Amazon EC2 User Guide for Linux Instances* . Conditional: This parameter is required when the volume type is ``io1`` . (Not used with ``standard`` , ``gp2`` , ``st1`` , or ``sc1`` volumes.) - **Encrypted** *(boolean) --* Specifies whether the volume should be encrypted. Encrypted EBS volumes must be attached to instances that support Amazon EBS encryption. Volumes that are created from encrypted snapshots are automatically encrypted. There is no way to create an encrypted volume from an unencrypted snapshot or an unencrypted volume from an encrypted snapshot. If your AMI uses encrypted volumes, you can only launch it on supported instance types. For more information, see `Amazon EBS Encryption <https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/EBSEncryption.html>`__ in the *Amazon EC2 User Guide for Linux Instances* . - **NoDevice** *(boolean) --* Suppresses a device mapping. If this parameter is true for the root device, the instance might fail the EC2 health check. In that case, Amazon EC2 Auto Scaling launches a replacement instance. :type InstanceMonitoring: dict :param InstanceMonitoring: Enables detailed monitoring (``true`` ) or basic monitoring (``false`` ) for the Auto Scaling instances. The default value is ``true`` . - **Enabled** *(boolean) --* If ``true`` , detailed monitoring is enabled. Otherwise, basic monitoring is enabled. :type SpotPrice: string :param SpotPrice: The maximum hourly price to be paid for any Spot Instance launched to fulfill the request. Spot Instances are launched when the price you specify exceeds the current Spot market price. For more information, see `Launching Spot Instances in Your Auto Scaling Group <https://docs.aws.amazon.com/autoscaling/ec2/userguide/asg-launch-spot-instances.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . :type IamInstanceProfile: string :param IamInstanceProfile: The name or the Amazon Resource Name (ARN) of the instance profile associated with the IAM role for the instance. EC2 instances launched with an IAM role automatically have AWS security credentials available. You can use IAM roles with Amazon EC2 Auto Scaling to automatically enable applications running on your EC2 instances to securely access other AWS resources. For more information, see `Use an IAM Role for Applications That Run on Amazon EC2 Instances <https://docs.aws.amazon.com/autoscaling/ec2/userguide/us-iam-role.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . :type EbsOptimized: boolean :param EbsOptimized: Indicates whether the instance is optimized for Amazon EBS I/O. By default, the instance is not optimized for EBS I/O. The optimization provides dedicated throughput to Amazon EBS and an optimized configuration stack to provide optimal I/O performance. This optimization is not available with all instance types. Additional usage charges apply. For more information, see `Amazon EBS-Optimized Instances <https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/EBSOptimized.html>`__ in the *Amazon EC2 User Guide for Linux Instances* . :type AssociatePublicIpAddress: boolean :param AssociatePublicIpAddress: Used for groups that launch instances into a virtual private cloud (VPC). Specifies whether to assign a public IP address to each instance. For more information, see `Launching Auto Scaling Instances in a VPC <https://docs.aws.amazon.com/autoscaling/ec2/userguide/asg-in-vpc.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . If you specify this parameter, be sure to specify at least one subnet when you create your group. Default: If the instance is launched into a default subnet, the default is to assign a public IP address. If the instance is launched into a nondefault subnet, the default is not to assign a public IP address. :type PlacementTenancy: string :param PlacementTenancy: The tenancy of the instance. An instance with a tenancy of ``dedicated`` runs on single-tenant hardware and can only be launched into a VPC. To launch Dedicated Instances into a shared tenancy VPC (a VPC with the instance placement tenancy attribute set to ``default`` ), you must set the value of this parameter to ``dedicated`` . If you specify this parameter, be sure to specify at least one subnet when you create your group. For more information, see `Launching Auto Scaling Instances in a VPC <https://docs.aws.amazon.com/autoscaling/ec2/userguide/asg-in-vpc.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . Valid values: ``default`` | ``dedicated`` :returns: None """ pass def create_or_update_tags(self, Tags: List): """ Creates or updates tags for the specified Auto Scaling group. When you specify a tag with a key that already exists, the operation overwrites the previous tag definition, and you do not get an error message. For more information, see `Tagging Auto Scaling Groups and Instances <https://docs.aws.amazon.com/autoscaling/ec2/userguide/autoscaling-tagging.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/CreateOrUpdateTags>`_ **Request Syntax** :: response = client.create_or_update_tags( Tags=[ { 'ResourceId': 'string', 'ResourceType': 'string', 'Key': 'string', 'Value': 'string', 'PropagateAtLaunch': True|False }, ] ) :type Tags: list :param Tags: **[REQUIRED]** One or more tags. - *(dict) --* Describes a tag for an Auto Scaling group. - **ResourceId** *(string) --* The name of the group. - **ResourceType** *(string) --* The type of resource. The only supported value is ``auto-scaling-group`` . - **Key** *(string) --* **[REQUIRED]** The tag key. - **Value** *(string) --* The tag value. - **PropagateAtLaunch** *(boolean) --* Determines whether the tag is added to new instances as they are launched in the group. :returns: None """ pass def delete_auto_scaling_group(self, AutoScalingGroupName: str, ForceDelete: bool = None): """ Deletes the specified Auto Scaling group. If the group has instances or scaling activities in progress, you must specify the option to force the deletion in order for it to succeed. If the group has policies, deleting the group deletes the policies, the underlying alarm actions, and any alarm that no longer has an associated action. To remove instances from the Auto Scaling group before deleting it, call DetachInstances with the list of instances and the option to decrement the desired capacity. This ensures that Amazon EC2 Auto Scaling does not launch replacement instances. To terminate all instances before deleting the Auto Scaling group, call UpdateAutoScalingGroup and set the minimum size and desired capacity of the Auto Scaling group to zero. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/DeleteAutoScalingGroup>`_ **Request Syntax** :: response = client.delete_auto_scaling_group( AutoScalingGroupName='string', ForceDelete=True|False ) :type AutoScalingGroupName: string :param AutoScalingGroupName: **[REQUIRED]** The name of the Auto Scaling group. :type ForceDelete: boolean :param ForceDelete: Specifies that the group is to be deleted along with all instances associated with the group, without waiting for all instances to be terminated. This parameter also deletes any lifecycle actions associated with the group. :returns: None """ pass def delete_launch_configuration(self, LaunchConfigurationName: str): """ Deletes the specified launch configuration. The launch configuration must not be attached to an Auto Scaling group. When this call completes, the launch configuration is no longer available for use. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/DeleteLaunchConfiguration>`_ **Request Syntax** :: response = client.delete_launch_configuration( LaunchConfigurationName='string' ) :type LaunchConfigurationName: string :param LaunchConfigurationName: **[REQUIRED]** The name of the launch configuration. :returns: None """ pass def delete_lifecycle_hook(self, LifecycleHookName: str, AutoScalingGroupName: str) -> Dict: """ Deletes the specified lifecycle hook. If there are any outstanding lifecycle actions, they are completed first (``ABANDON`` for launching instances, ``CONTINUE`` for terminating instances). See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/DeleteLifecycleHook>`_ **Request Syntax** :: response = client.delete_lifecycle_hook( LifecycleHookName='string', AutoScalingGroupName='string' ) **Response Syntax** :: {} **Response Structure** - *(dict) --* :type LifecycleHookName: string :param LifecycleHookName: **[REQUIRED]** The name of the lifecycle hook. :type AutoScalingGroupName: string :param AutoScalingGroupName: **[REQUIRED]** The name of the Auto Scaling group. :rtype: dict :returns: """ pass def delete_notification_configuration(self, AutoScalingGroupName: str, TopicARN: str): """ Deletes the specified notification. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/DeleteNotificationConfiguration>`_ **Request Syntax** :: response = client.delete_notification_configuration( AutoScalingGroupName='string', TopicARN='string' ) :type AutoScalingGroupName: string :param AutoScalingGroupName: **[REQUIRED]** The name of the Auto Scaling group. :type TopicARN: string :param TopicARN: **[REQUIRED]** The Amazon Resource Name (ARN) of the Amazon Simple Notification Service (Amazon SNS) topic. :returns: None """ pass def delete_policy(self, PolicyName: str, AutoScalingGroupName: str = None): """ Deletes the specified scaling policy. Deleting a policy deletes the underlying alarm action, but does not delete the alarm, even if it no longer has an associated action. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/DeletePolicy>`_ **Request Syntax** :: response = client.delete_policy( AutoScalingGroupName='string', PolicyName='string' ) :type AutoScalingGroupName: string :param AutoScalingGroupName: The name of the Auto Scaling group. :type PolicyName: string :param PolicyName: **[REQUIRED]** The name or Amazon Resource Name (ARN) of the policy. :returns: None """ pass def delete_scheduled_action(self, AutoScalingGroupName: str, ScheduledActionName: str): """ Deletes the specified scheduled action. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/DeleteScheduledAction>`_ **Request Syntax** :: response = client.delete_scheduled_action( AutoScalingGroupName='string', ScheduledActionName='string' ) :type AutoScalingGroupName: string :param AutoScalingGroupName: **[REQUIRED]** The name of the Auto Scaling group. :type ScheduledActionName: string :param ScheduledActionName: **[REQUIRED]** The name of the action to delete. :returns: None """ pass def delete_tags(self, Tags: List): """ Deletes the specified tags. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/DeleteTags>`_ **Request Syntax** :: response = client.delete_tags( Tags=[ { 'ResourceId': 'string', 'ResourceType': 'string', 'Key': 'string', 'Value': 'string', 'PropagateAtLaunch': True|False }, ] ) :type Tags: list :param Tags: **[REQUIRED]** One or more tags. - *(dict) --* Describes a tag for an Auto Scaling group. - **ResourceId** *(string) --* The name of the group. - **ResourceType** *(string) --* The type of resource. The only supported value is ``auto-scaling-group`` . - **Key** *(string) --* **[REQUIRED]** The tag key. - **Value** *(string) --* The tag value. - **PropagateAtLaunch** *(boolean) --* Determines whether the tag is added to new instances as they are launched in the group. :returns: None """ pass def describe_account_limits(self) -> Dict: """ Describes the current Amazon EC2 Auto Scaling resource limits for your AWS account. For information about requesting an increase in these limits, see `Amazon EC2 Auto Scaling Limits <https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-account-limits.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/DescribeAccountLimits>`_ **Request Syntax** :: response = client.describe_account_limits() **Response Syntax** :: { 'MaxNumberOfAutoScalingGroups': 123, 'MaxNumberOfLaunchConfigurations': 123, 'NumberOfAutoScalingGroups': 123, 'NumberOfLaunchConfigurations': 123 } **Response Structure** - *(dict) --* - **MaxNumberOfAutoScalingGroups** *(integer) --* The maximum number of groups allowed for your AWS account. The default limit is 200 per region. - **MaxNumberOfLaunchConfigurations** *(integer) --* The maximum number of launch configurations allowed for your AWS account. The default limit is 200 per region. - **NumberOfAutoScalingGroups** *(integer) --* The current number of groups for your AWS account. - **NumberOfLaunchConfigurations** *(integer) --* The current number of launch configurations for your AWS account. :rtype: dict :returns: """ pass def describe_adjustment_types(self) -> Dict: """ Describes the policy adjustment types for use with PutScalingPolicy . See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/DescribeAdjustmentTypes>`_ **Request Syntax** :: response = client.describe_adjustment_types() **Response Syntax** :: { 'AdjustmentTypes': [ { 'AdjustmentType': 'string' }, ] } **Response Structure** - *(dict) --* - **AdjustmentTypes** *(list) --* The policy adjustment types. - *(dict) --* Describes a policy adjustment type. - **AdjustmentType** *(string) --* The policy adjustment type. The valid values are ``ChangeInCapacity`` , ``ExactCapacity`` , and ``PercentChangeInCapacity`` . :rtype: dict :returns: """ pass def describe_auto_scaling_groups(self, AutoScalingGroupNames: List = None, NextToken: str = None, MaxRecords: int = None) -> Dict: """ Describes one or more Auto Scaling groups. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/DescribeAutoScalingGroups>`_ **Request Syntax** :: response = client.describe_auto_scaling_groups( AutoScalingGroupNames=[ 'string', ], NextToken='string', MaxRecords=123 ) **Response Syntax** :: { 'AutoScalingGroups': [ { 'AutoScalingGroupName': 'string', 'AutoScalingGroupARN': 'string', 'LaunchConfigurationName': 'string', 'LaunchTemplate': { 'LaunchTemplateId': 'string', 'LaunchTemplateName': 'string', 'Version': 'string' }, 'MixedInstancesPolicy': { 'LaunchTemplate': { 'LaunchTemplateSpecification': { 'LaunchTemplateId': 'string', 'LaunchTemplateName': 'string', 'Version': 'string' }, 'Overrides': [ { 'InstanceType': 'string' }, ] }, 'InstancesDistribution': { 'OnDemandAllocationStrategy': 'string', 'OnDemandBaseCapacity': 123, 'OnDemandPercentageAboveBaseCapacity': 123, 'SpotAllocationStrategy': 'string', 'SpotInstancePools': 123, 'SpotMaxPrice': 'string' } }, 'MinSize': 123, 'MaxSize': 123, 'DesiredCapacity': 123, 'DefaultCooldown': 123, 'AvailabilityZones': [ 'string', ], 'LoadBalancerNames': [ 'string', ], 'TargetGroupARNs': [ 'string', ], 'HealthCheckType': 'string', 'HealthCheckGracePeriod': 123, 'Instances': [ { 'InstanceId': 'string', 'AvailabilityZone': 'string', 'LifecycleState': 'Pending'|'Pending:Wait'|'Pending:Proceed'|'Quarantined'|'InService'|'Terminating'|'Terminating:Wait'|'Terminating:Proceed'|'Terminated'|'Detaching'|'Detached'|'EnteringStandby'|'Standby', 'HealthStatus': 'string', 'LaunchConfigurationName': 'string', 'LaunchTemplate': { 'LaunchTemplateId': 'string', 'LaunchTemplateName': 'string', 'Version': 'string' }, 'ProtectedFromScaleIn': True|False }, ], 'CreatedTime': datetime(2015, 1, 1), 'SuspendedProcesses': [ { 'ProcessName': 'string', 'SuspensionReason': 'string' }, ], 'PlacementGroup': 'string', 'VPCZoneIdentifier': 'string', 'EnabledMetrics': [ { 'Metric': 'string', 'Granularity': 'string' }, ], 'Status': 'string', 'Tags': [ { 'ResourceId': 'string', 'ResourceType': 'string', 'Key': 'string', 'Value': 'string', 'PropagateAtLaunch': True|False }, ], 'TerminationPolicies': [ 'string', ], 'NewInstancesProtectedFromScaleIn': True|False, 'ServiceLinkedRoleARN': 'string' }, ], 'NextToken': 'string' } **Response Structure** - *(dict) --* - **AutoScalingGroups** *(list) --* The groups. - *(dict) --* Describes an Auto Scaling group. - **AutoScalingGroupName** *(string) --* The name of the Auto Scaling group. - **AutoScalingGroupARN** *(string) --* The Amazon Resource Name (ARN) of the Auto Scaling group. - **LaunchConfigurationName** *(string) --* The name of the associated launch configuration. - **LaunchTemplate** *(dict) --* The launch template for the group. - **LaunchTemplateId** *(string) --* The ID of the launch template. You must specify either a template ID or a template name. - **LaunchTemplateName** *(string) --* The name of the launch template. You must specify either a template name or a template ID. - **Version** *(string) --* The version number, ``$Latest`` , or ``$Default`` . If the value is ``$Latest`` , Amazon EC2 Auto Scaling selects the latest version of the launch template when launching instances. If the value is ``$Default`` , Amazon EC2 Auto Scaling selects the default version of the launch template when launching instances. The default value is ``$Default`` . - **MixedInstancesPolicy** *(dict) --* The mixed instances policy for the group. - **LaunchTemplate** *(dict) --* The launch template and overrides. This parameter is required when creating an Auto Scaling group with a mixed instances policy, but is not required when updating the group. - **LaunchTemplateSpecification** *(dict) --* The launch template to use. You must specify either the launch template ID or launch template name in the request. - **LaunchTemplateId** *(string) --* The ID of the launch template. You must specify either a template ID or a template name. - **LaunchTemplateName** *(string) --* The name of the launch template. You must specify either a template name or a template ID. - **Version** *(string) --* The version number, ``$Latest`` , or ``$Default`` . If the value is ``$Latest`` , Amazon EC2 Auto Scaling selects the latest version of the launch template when launching instances. If the value is ``$Default`` , Amazon EC2 Auto Scaling selects the default version of the launch template when launching instances. The default value is ``$Default`` . - **Overrides** *(list) --* Any parameters that you specify override the same parameters in the launch template. Currently, the only supported override is instance type. You must specify between 2 and 20 overrides. - *(dict) --* Describes an override for a launch template. - **InstanceType** *(string) --* The instance type. For information about available instance types, see `Available Instance Types <https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/instance-types.html#AvailableInstanceTypes>`__ in the *Amazon Elastic Compute Cloud User Guide.* - **InstancesDistribution** *(dict) --* The instances distribution to use. If you leave this parameter unspecified when creating the group, the default values are used. - **OnDemandAllocationStrategy** *(string) --* Indicates how to allocate instance types to fulfill On-Demand capacity. The only valid value is ``prioritized`` , which is also the default value. This strategy uses the order of instance type overrides for the LaunchTemplate to define the launch priority of each instance type. The first instance type in the array is prioritized higher than the last. If all your On-Demand capacity cannot be fulfilled using your highest priority instance, then the Auto Scaling groups launches the remaining capacity using the second priority instance type, and so on. - **OnDemandBaseCapacity** *(integer) --* The minimum amount of the Auto Scaling group's capacity that must be fulfilled by On-Demand Instances. This base portion is provisioned first as your group scales. The default value is ``0`` . If you leave this parameter set to ``0`` , On-Demand Instances are launched as a percentage of the Auto Scaling group's desired capacity, per the ``OnDemandPercentageAboveBaseCapacity`` setting. - **OnDemandPercentageAboveBaseCapacity** *(integer) --* Controls the percentages of On-Demand Instances and Spot Instances for your additional capacity beyond ``OnDemandBaseCapacity`` . The range is 0–100. The default value is ``100`` . If you leave this parameter set to ``100`` , the percentages are 100% for On-Demand Instances and 0% for Spot Instances. - **SpotAllocationStrategy** *(string) --* Indicates how to allocate Spot capacity across Spot pools. The only valid value is ``lowest-price`` , which is also the default value. The Auto Scaling group selects the cheapest Spot pools and evenly allocates your Spot capacity across the number of Spot pools that you specify. - **SpotInstancePools** *(integer) --* The number of Spot pools to use to allocate your Spot capacity. The Spot pools are determined from the different instance types in the Overrides array of LaunchTemplate . The range is 1–20 and the default is 2. - **SpotMaxPrice** *(string) --* The maximum price per unit hour that you are willing to pay for a Spot Instance. If you leave the value of this parameter blank (which is the default), the maximum Spot price is set at the On-Demand price. To remove a value that you previously set, include the parameter but leave the value blank. - **MinSize** *(integer) --* The minimum size of the group. - **MaxSize** *(integer) --* The maximum size of the group. - **DesiredCapacity** *(integer) --* The desired size of the group. - **DefaultCooldown** *(integer) --* The amount of time, in seconds, after a scaling activity completes before another scaling activity can start. - **AvailabilityZones** *(list) --* One or more Availability Zones for the group. - *(string) --* - **LoadBalancerNames** *(list) --* One or more load balancers associated with the group. - *(string) --* - **TargetGroupARNs** *(list) --* The Amazon Resource Names (ARN) of the target groups for your load balancer. - *(string) --* - **HealthCheckType** *(string) --* The service to use for the health checks. The valid values are ``EC2`` and ``ELB`` . If you configure an Auto Scaling group to use ELB health checks, it considers the instance unhealthy if it fails either the EC2 status checks or the load balancer health checks. - **HealthCheckGracePeriod** *(integer) --* The amount of time, in seconds, that Amazon EC2 Auto Scaling waits before checking the health status of an EC2 instance that has come into service. - **Instances** *(list) --* The EC2 instances associated with the group. - *(dict) --* Describes an EC2 instance. - **InstanceId** *(string) --* The ID of the instance. - **AvailabilityZone** *(string) --* The Availability Zone in which the instance is running. - **LifecycleState** *(string) --* A description of the current lifecycle state. The ``Quarantined`` state is not used. - **HealthStatus** *(string) --* The last reported health status of the instance. "Healthy" means that the instance is healthy and should remain in service. "Unhealthy" means that the instance is unhealthy and that Amazon EC2 Auto Scaling should terminate and replace it. - **LaunchConfigurationName** *(string) --* The launch configuration associated with the instance. - **LaunchTemplate** *(dict) --* The launch template for the instance. - **LaunchTemplateId** *(string) --* The ID of the launch template. You must specify either a template ID or a template name. - **LaunchTemplateName** *(string) --* The name of the launch template. You must specify either a template name or a template ID. - **Version** *(string) --* The version number, ``$Latest`` , or ``$Default`` . If the value is ``$Latest`` , Amazon EC2 Auto Scaling selects the latest version of the launch template when launching instances. If the value is ``$Default`` , Amazon EC2 Auto Scaling selects the default version of the launch template when launching instances. The default value is ``$Default`` . - **ProtectedFromScaleIn** *(boolean) --* Indicates whether the instance is protected from termination by Amazon EC2 Auto Scaling when scaling in. - **CreatedTime** *(datetime) --* The date and time the group was created. - **SuspendedProcesses** *(list) --* The suspended processes associated with the group. - *(dict) --* Describes an automatic scaling process that has been suspended. For more information, see ProcessType . - **ProcessName** *(string) --* The name of the suspended process. - **SuspensionReason** *(string) --* The reason that the process was suspended. - **PlacementGroup** *(string) --* The name of the placement group into which to launch your instances, if any. - **VPCZoneIdentifier** *(string) --* One or more subnet IDs, if applicable, separated by commas. - **EnabledMetrics** *(list) --* The metrics enabled for the group. - *(dict) --* Describes an enabled metric. - **Metric** *(string) --* One of the following metrics: * ``GroupMinSize`` * ``GroupMaxSize`` * ``GroupDesiredCapacity`` * ``GroupInServiceInstances`` * ``GroupPendingInstances`` * ``GroupStandbyInstances`` * ``GroupTerminatingInstances`` * ``GroupTotalInstances`` - **Granularity** *(string) --* The granularity of the metric. The only valid value is ``1Minute`` . - **Status** *(string) --* The current state of the group when DeleteAutoScalingGroup is in progress. - **Tags** *(list) --* The tags for the group. - *(dict) --* Describes a tag for an Auto Scaling group. - **ResourceId** *(string) --* The name of the group. - **ResourceType** *(string) --* The type of resource. The only supported value is ``auto-scaling-group`` . - **Key** *(string) --* The tag key. - **Value** *(string) --* The tag value. - **PropagateAtLaunch** *(boolean) --* Determines whether the tag is added to new instances as they are launched in the group. - **TerminationPolicies** *(list) --* The termination policies for the group. - *(string) --* - **NewInstancesProtectedFromScaleIn** *(boolean) --* Indicates whether newly launched instances are protected from termination by Amazon EC2 Auto Scaling when scaling in. - **ServiceLinkedRoleARN** *(string) --* The Amazon Resource Name (ARN) of the service-linked role that the Auto Scaling group uses to call other AWS services on your behalf. - **NextToken** *(string) --* A string that indicates that the response contains more items than can be returned in a single response. To receive additional items, specify this string for the ``NextToken`` value when requesting the next set of items. This value is null when there are no more items to return. :type AutoScalingGroupNames: list :param AutoScalingGroupNames: The names of the Auto Scaling groups. Each name can be a maximum of 1600 characters. By default, you can only specify up to 50 names. You can optionally increase this limit using the ``MaxRecords`` parameter. If you omit this parameter, all Auto Scaling groups are described. - *(string) --* :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :type MaxRecords: integer :param MaxRecords: The maximum number of items to return with this call. The default value is ``50`` and the maximum value is ``100`` . :rtype: dict :returns: """ pass def describe_auto_scaling_instances(self, InstanceIds: List = None, MaxRecords: int = None, NextToken: str = None) -> Dict: """ Describes one or more Auto Scaling instances. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/DescribeAutoScalingInstances>`_ **Request Syntax** :: response = client.describe_auto_scaling_instances( InstanceIds=[ 'string', ], MaxRecords=123, NextToken='string' ) **Response Syntax** :: { 'AutoScalingInstances': [ { 'InstanceId': 'string', 'AutoScalingGroupName': 'string', 'AvailabilityZone': 'string', 'LifecycleState': 'string', 'HealthStatus': 'string', 'LaunchConfigurationName': 'string', 'LaunchTemplate': { 'LaunchTemplateId': 'string', 'LaunchTemplateName': 'string', 'Version': 'string' }, 'ProtectedFromScaleIn': True|False }, ], 'NextToken': 'string' } **Response Structure** - *(dict) --* - **AutoScalingInstances** *(list) --* The instances. - *(dict) --* Describes an EC2 instance associated with an Auto Scaling group. - **InstanceId** *(string) --* The ID of the instance. - **AutoScalingGroupName** *(string) --* The name of the Auto Scaling group for the instance. - **AvailabilityZone** *(string) --* The Availability Zone for the instance. - **LifecycleState** *(string) --* The lifecycle state for the instance. - **HealthStatus** *(string) --* The last reported health status of this instance. "Healthy" means that the instance is healthy and should remain in service. "Unhealthy" means that the instance is unhealthy and Amazon EC2 Auto Scaling should terminate and replace it. - **LaunchConfigurationName** *(string) --* The launch configuration used to launch the instance. This value is not available if you attached the instance to the Auto Scaling group. - **LaunchTemplate** *(dict) --* The launch template for the instance. - **LaunchTemplateId** *(string) --* The ID of the launch template. You must specify either a template ID or a template name. - **LaunchTemplateName** *(string) --* The name of the launch template. You must specify either a template name or a template ID. - **Version** *(string) --* The version number, ``$Latest`` , or ``$Default`` . If the value is ``$Latest`` , Amazon EC2 Auto Scaling selects the latest version of the launch template when launching instances. If the value is ``$Default`` , Amazon EC2 Auto Scaling selects the default version of the launch template when launching instances. The default value is ``$Default`` . - **ProtectedFromScaleIn** *(boolean) --* Indicates whether the instance is protected from termination by Amazon EC2 Auto Scaling when scaling in. - **NextToken** *(string) --* A string that indicates that the response contains more items than can be returned in a single response. To receive additional items, specify this string for the ``NextToken`` value when requesting the next set of items. This value is null when there are no more items to return. :type InstanceIds: list :param InstanceIds: The IDs of the instances. You can specify up to ``MaxRecords`` IDs. If you omit this parameter, all Auto Scaling instances are described. If you specify an ID that does not exist, it is ignored with no error. - *(string) --* :type MaxRecords: integer :param MaxRecords: The maximum number of items to return with this call. The default value is ``50`` and the maximum value is ``50`` . :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :rtype: dict :returns: """ pass def describe_auto_scaling_notification_types(self) -> Dict: """ Describes the notification types that are supported by Amazon EC2 Auto Scaling. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/DescribeAutoScalingNotificationTypes>`_ **Request Syntax** :: response = client.describe_auto_scaling_notification_types() **Response Syntax** :: { 'AutoScalingNotificationTypes': [ 'string', ] } **Response Structure** - *(dict) --* - **AutoScalingNotificationTypes** *(list) --* The notification types. - *(string) --* :rtype: dict :returns: """ pass def describe_launch_configurations(self, LaunchConfigurationNames: List = None, NextToken: str = None, MaxRecords: int = None) -> Dict: """ Describes one or more launch configurations. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/DescribeLaunchConfigurations>`_ **Request Syntax** :: response = client.describe_launch_configurations( LaunchConfigurationNames=[ 'string', ], NextToken='string', MaxRecords=123 ) **Response Syntax** :: { 'LaunchConfigurations': [ { 'LaunchConfigurationName': 'string', 'LaunchConfigurationARN': 'string', 'ImageId': 'string', 'KeyName': 'string', 'SecurityGroups': [ 'string', ], 'ClassicLinkVPCId': 'string', 'ClassicLinkVPCSecurityGroups': [ 'string', ], 'UserData': 'string', 'InstanceType': 'string', 'KernelId': 'string', 'RamdiskId': 'string', 'BlockDeviceMappings': [ { 'VirtualName': 'string', 'DeviceName': 'string', 'Ebs': { 'SnapshotId': 'string', 'VolumeSize': 123, 'VolumeType': 'string', 'DeleteOnTermination': True|False, 'Iops': 123, 'Encrypted': True|False }, 'NoDevice': True|False }, ], 'InstanceMonitoring': { 'Enabled': True|False }, 'SpotPrice': 'string', 'IamInstanceProfile': 'string', 'CreatedTime': datetime(2015, 1, 1), 'EbsOptimized': True|False, 'AssociatePublicIpAddress': True|False, 'PlacementTenancy': 'string' }, ], 'NextToken': 'string' } **Response Structure** - *(dict) --* - **LaunchConfigurations** *(list) --* The launch configurations. - *(dict) --* Describes a launch configuration. - **LaunchConfigurationName** *(string) --* The name of the launch configuration. - **LaunchConfigurationARN** *(string) --* The Amazon Resource Name (ARN) of the launch configuration. - **ImageId** *(string) --* The ID of the Amazon Machine Image (AMI). - **KeyName** *(string) --* The name of the key pair. - **SecurityGroups** *(list) --* The security groups to associate with the instances. - *(string) --* - **ClassicLinkVPCId** *(string) --* The ID of a ClassicLink-enabled VPC to link your EC2-Classic instances to. This parameter can only be used if you are launching EC2-Classic instances. For more information, see `ClassicLink <https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/vpc-classiclink.html>`__ in the *Amazon EC2 User Guide for Linux Instances* and `Linking EC2-Classic Instances to a VPC <https://docs.aws.amazon.com/autoscaling/ec2/userguide/asg-in-vpc.html#as-ClassicLink>`__ in the *Amazon EC2 Auto Scaling User Guide* . - **ClassicLinkVPCSecurityGroups** *(list) --* The IDs of one or more security groups for the VPC specified in ``ClassicLinkVPCId`` . For more information, see `ClassicLink <https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/vpc-classiclink.html>`__ in the *Amazon EC2 User Guide for Linux Instances* and `Linking EC2-Classic Instances to a VPC <https://docs.aws.amazon.com/autoscaling/ec2/userguide/asg-in-vpc.html#as-ClassicLink>`__ in the *Amazon EC2 Auto Scaling User Guide* . Conditional: This parameter is required if you specify a ClassicLink-enabled VPC, and cannot be used otherwise. - *(string) --* - **UserData** *(string) --* The user data available to the instances. - **InstanceType** *(string) --* The instance type for the instances. - **KernelId** *(string) --* The ID of the kernel associated with the AMI. - **RamdiskId** *(string) --* The ID of the RAM disk associated with the AMI. - **BlockDeviceMappings** *(list) --* A block device mapping, which specifies the block devices for the instance. - *(dict) --* Describes a block device mapping. - **VirtualName** *(string) --* The name of the virtual device (for example, ``ephemeral0`` ). - **DeviceName** *(string) --* The device name exposed to the EC2 instance (for example, ``/dev/sdh`` or ``xvdh`` ). For more information, see `Device Naming on Linux Instances <https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/device_naming.html>`__ in the *Amazon EC2 User Guide for Linux Instances* . - **Ebs** *(dict) --* The information about the Amazon EBS volume. - **SnapshotId** *(string) --* The ID of the snapshot. This parameter is optional if you specify a volume size. - **VolumeSize** *(integer) --* The volume size, in GiB. Constraints: 1-1,024 for ``standard`` , 4-16,384 for ``io1`` , 1-16,384 for ``gp2`` , and 500-16,384 for ``st1`` and ``sc1`` . If you specify a snapshot, the volume size must be equal to or larger than the snapshot size. Default: If you create a volume from a snapshot and you don't specify a volume size, the default is the snapshot size. .. note:: At least one of VolumeSize or SnapshotId is required. - **VolumeType** *(string) --* The volume type, which can be ``standard`` for Magnetic, ``io1`` for Provisioned IOPS SSD, ``gp2`` for General Purpose SSD, ``st1`` for Throughput Optimized HDD, or ``sc1`` for Cold HDD. For more information, see `Amazon EBS Volume Types <https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/EBSVolumeTypes.html>`__ in the *Amazon EC2 User Guide for Linux Instances* . Valid values: ``standard`` | ``io1`` | ``gp2`` | ``st1`` | ``sc1`` - **DeleteOnTermination** *(boolean) --* Indicates whether the volume is deleted on instance termination. The default value is ``true`` . - **Iops** *(integer) --* The number of I/O operations per second (IOPS) to provision for the volume. For more information, see `Amazon EBS Volume Types <https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/EBSVolumeTypes.html>`__ in the *Amazon EC2 User Guide for Linux Instances* . Conditional: This parameter is required when the volume type is ``io1`` . (Not used with ``standard`` , ``gp2`` , ``st1`` , or ``sc1`` volumes.) - **Encrypted** *(boolean) --* Specifies whether the volume should be encrypted. Encrypted EBS volumes must be attached to instances that support Amazon EBS encryption. Volumes that are created from encrypted snapshots are automatically encrypted. There is no way to create an encrypted volume from an unencrypted snapshot or an unencrypted volume from an encrypted snapshot. If your AMI uses encrypted volumes, you can only launch it on supported instance types. For more information, see `Amazon EBS Encryption <https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/EBSEncryption.html>`__ in the *Amazon EC2 User Guide for Linux Instances* . - **NoDevice** *(boolean) --* Suppresses a device mapping. If this parameter is true for the root device, the instance might fail the EC2 health check. In that case, Amazon EC2 Auto Scaling launches a replacement instance. - **InstanceMonitoring** *(dict) --* Controls whether instances in this group are launched with detailed (``true`` ) or basic (``false`` ) monitoring. - **Enabled** *(boolean) --* If ``true`` , detailed monitoring is enabled. Otherwise, basic monitoring is enabled. - **SpotPrice** *(string) --* The price to bid when launching Spot Instances. - **IamInstanceProfile** *(string) --* The name or Amazon Resource Name (ARN) of the instance profile associated with the IAM role for the instance. - **CreatedTime** *(datetime) --* The creation date and time for the launch configuration. - **EbsOptimized** *(boolean) --* Controls whether the instance is optimized for EBS I/O (``true`` ) or not (``false`` ). - **AssociatePublicIpAddress** *(boolean) --* [EC2-VPC] Indicates whether to assign a public IP address to each instance. - **PlacementTenancy** *(string) --* The tenancy of the instance, either ``default`` or ``dedicated`` . An instance with ``dedicated`` tenancy runs in an isolated, single-tenant hardware and can only be launched into a VPC. - **NextToken** *(string) --* A string that indicates that the response contains more items than can be returned in a single response. To receive additional items, specify this string for the ``NextToken`` value when requesting the next set of items. This value is null when there are no more items to return. :type LaunchConfigurationNames: list :param LaunchConfigurationNames: The launch configuration names. If you omit this parameter, all launch configurations are described. - *(string) --* :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :type MaxRecords: integer :param MaxRecords: The maximum number of items to return with this call. The default value is ``50`` and the maximum value is ``100`` . :rtype: dict :returns: """ pass def describe_lifecycle_hook_types(self) -> Dict: """ Describes the available types of lifecycle hooks. The following hook types are supported: * autoscaling:EC2_INSTANCE_LAUNCHING * autoscaling:EC2_INSTANCE_TERMINATING See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/DescribeLifecycleHookTypes>`_ **Request Syntax** :: response = client.describe_lifecycle_hook_types() **Response Syntax** :: { 'LifecycleHookTypes': [ 'string', ] } **Response Structure** - *(dict) --* - **LifecycleHookTypes** *(list) --* The lifecycle hook types. - *(string) --* :rtype: dict :returns: """ pass def describe_lifecycle_hooks(self, AutoScalingGroupName: str, LifecycleHookNames: List = None) -> Dict: """ Describes the lifecycle hooks for the specified Auto Scaling group. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/DescribeLifecycleHooks>`_ **Request Syntax** :: response = client.describe_lifecycle_hooks( AutoScalingGroupName='string', LifecycleHookNames=[ 'string', ] ) **Response Syntax** :: { 'LifecycleHooks': [ { 'LifecycleHookName': 'string', 'AutoScalingGroupName': 'string', 'LifecycleTransition': 'string', 'NotificationTargetARN': 'string', 'RoleARN': 'string', 'NotificationMetadata': 'string', 'HeartbeatTimeout': 123, 'GlobalTimeout': 123, 'DefaultResult': 'string' }, ] } **Response Structure** - *(dict) --* - **LifecycleHooks** *(list) --* The lifecycle hooks for the specified group. - *(dict) --* Describes a lifecycle hook, which tells Amazon EC2 Auto Scaling that you want to perform an action whenever it launches instances or whenever it terminates instances. Used in response to DescribeLifecycleHooks . - **LifecycleHookName** *(string) --* The name of the lifecycle hook. - **AutoScalingGroupName** *(string) --* The name of the Auto Scaling group for the lifecycle hook. - **LifecycleTransition** *(string) --* The state of the EC2 instance to which to attach the lifecycle hook. The following are possible values: * autoscaling:EC2_INSTANCE_LAUNCHING * autoscaling:EC2_INSTANCE_TERMINATING - **NotificationTargetARN** *(string) --* The ARN of the target that Amazon EC2 Auto Scaling sends notifications to when an instance is in the transition state for the lifecycle hook. The notification target can be either an SQS queue or an SNS topic. - **RoleARN** *(string) --* The ARN of the IAM role that allows the Auto Scaling group to publish to the specified notification target. - **NotificationMetadata** *(string) --* Additional information that is included any time Amazon EC2 Auto Scaling sends a message to the notification target. - **HeartbeatTimeout** *(integer) --* The maximum time, in seconds, that can elapse before the lifecycle hook times out. If the lifecycle hook times out, Amazon EC2 Auto Scaling performs the action that you specified in the ``DefaultResult`` parameter. - **GlobalTimeout** *(integer) --* The maximum time, in seconds, that an instance can remain in a ``Pending:Wait`` or ``Terminating:Wait`` state. The maximum is 172800 seconds (48 hours) or 100 times ``HeartbeatTimeout`` , whichever is smaller. - **DefaultResult** *(string) --* Defines the action the Auto Scaling group should take when the lifecycle hook timeout elapses or if an unexpected failure occurs. The possible values are ``CONTINUE`` and ``ABANDON`` . :type AutoScalingGroupName: string :param AutoScalingGroupName: **[REQUIRED]** The name of the Auto Scaling group. :type LifecycleHookNames: list :param LifecycleHookNames: The names of one or more lifecycle hooks. If you omit this parameter, all lifecycle hooks are described. - *(string) --* :rtype: dict :returns: """ pass def describe_load_balancer_target_groups(self, AutoScalingGroupName: str, NextToken: str = None, MaxRecords: int = None) -> Dict: """ Describes the target groups for the specified Auto Scaling group. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/DescribeLoadBalancerTargetGroups>`_ **Request Syntax** :: response = client.describe_load_balancer_target_groups( AutoScalingGroupName='string', NextToken='string', MaxRecords=123 ) **Response Syntax** :: { 'LoadBalancerTargetGroups': [ { 'LoadBalancerTargetGroupARN': 'string', 'State': 'string' }, ], 'NextToken': 'string' } **Response Structure** - *(dict) --* - **LoadBalancerTargetGroups** *(list) --* Information about the target groups. - *(dict) --* Describes the state of a target group. If you attach a target group to an existing Auto Scaling group, the initial state is ``Adding`` . The state transitions to ``Added`` after all Auto Scaling instances are registered with the target group. If Elastic Load Balancing health checks are enabled, the state transitions to ``InService`` after at least one Auto Scaling instance passes the health check. If EC2 health checks are enabled instead, the target group remains in the ``Added`` state. - **LoadBalancerTargetGroupARN** *(string) --* The Amazon Resource Name (ARN) of the target group. - **State** *(string) --* The state of the target group. * ``Adding`` - The Auto Scaling instances are being registered with the target group. * ``Added`` - All Auto Scaling instances are registered with the target group. * ``InService`` - At least one Auto Scaling instance passed an ELB health check. * ``Removing`` - The Auto Scaling instances are being deregistered from the target group. If connection draining is enabled, Elastic Load Balancing waits for in-flight requests to complete before deregistering the instances. * ``Removed`` - All Auto Scaling instances are deregistered from the target group. - **NextToken** *(string) --* A string that indicates that the response contains more items than can be returned in a single response. To receive additional items, specify this string for the ``NextToken`` value when requesting the next set of items. This value is null when there are no more items to return. :type AutoScalingGroupName: string :param AutoScalingGroupName: **[REQUIRED]** The name of the Auto Scaling group. :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :type MaxRecords: integer :param MaxRecords: The maximum number of items to return with this call. The default value is ``100`` and the maximum value is ``100`` . :rtype: dict :returns: """ pass def describe_load_balancers(self, AutoScalingGroupName: str, NextToken: str = None, MaxRecords: int = None) -> Dict: """ Describes the load balancers for the specified Auto Scaling group. This operation describes only Classic Load Balancers. If you have Application Load Balancers or Network Load Balancers, use DescribeLoadBalancerTargetGroups instead. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/DescribeLoadBalancers>`_ **Request Syntax** :: response = client.describe_load_balancers( AutoScalingGroupName='string', NextToken='string', MaxRecords=123 ) **Response Syntax** :: { 'LoadBalancers': [ { 'LoadBalancerName': 'string', 'State': 'string' }, ], 'NextToken': 'string' } **Response Structure** - *(dict) --* - **LoadBalancers** *(list) --* The load balancers. - *(dict) --* Describes the state of a Classic Load Balancer. If you specify a load balancer when creating the Auto Scaling group, the state of the load balancer is ``InService`` . If you attach a load balancer to an existing Auto Scaling group, the initial state is ``Adding`` . The state transitions to ``Added`` after all instances in the group are registered with the load balancer. If Elastic Load Balancing health checks are enabled for the load balancer, the state transitions to ``InService`` after at least one instance in the group passes the health check. If EC2 health checks are enabled instead, the load balancer remains in the ``Added`` state. - **LoadBalancerName** *(string) --* The name of the load balancer. - **State** *(string) --* One of the following load balancer states: * ``Adding`` - The instances in the group are being registered with the load balancer. * ``Added`` - All instances in the group are registered with the load balancer. * ``InService`` - At least one instance in the group passed an ELB health check. * ``Removing`` - The instances in the group are being deregistered from the load balancer. If connection draining is enabled, Elastic Load Balancing waits for in-flight requests to complete before deregistering the instances. * ``Removed`` - All instances in the group are deregistered from the load balancer. - **NextToken** *(string) --* A string that indicates that the response contains more items than can be returned in a single response. To receive additional items, specify this string for the ``NextToken`` value when requesting the next set of items. This value is null when there are no more items to return. :type AutoScalingGroupName: string :param AutoScalingGroupName: **[REQUIRED]** The name of the Auto Scaling group. :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :type MaxRecords: integer :param MaxRecords: The maximum number of items to return with this call. The default value is ``100`` and the maximum value is ``100`` . :rtype: dict :returns: """ pass def describe_metric_collection_types(self) -> Dict: """ Describes the available CloudWatch metrics for Amazon EC2 Auto Scaling. The ``GroupStandbyInstances`` metric is not returned by default. You must explicitly request this metric when calling EnableMetricsCollection . See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/DescribeMetricCollectionTypes>`_ **Request Syntax** :: response = client.describe_metric_collection_types() **Response Syntax** :: { 'Metrics': [ { 'Metric': 'string' }, ], 'Granularities': [ { 'Granularity': 'string' }, ] } **Response Structure** - *(dict) --* - **Metrics** *(list) --* One or more metrics. - *(dict) --* Describes a metric. - **Metric** *(string) --* One of the following metrics: * ``GroupMinSize`` * ``GroupMaxSize`` * ``GroupDesiredCapacity`` * ``GroupInServiceInstances`` * ``GroupPendingInstances`` * ``GroupStandbyInstances`` * ``GroupTerminatingInstances`` * ``GroupTotalInstances`` - **Granularities** *(list) --* The granularities for the metrics. - *(dict) --* Describes a granularity of a metric. - **Granularity** *(string) --* The granularity. The only valid value is ``1Minute`` . :rtype: dict :returns: """ pass def describe_notification_configurations(self, AutoScalingGroupNames: List = None, NextToken: str = None, MaxRecords: int = None) -> Dict: """ Describes the notification actions associated with the specified Auto Scaling group. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/DescribeNotificationConfigurations>`_ **Request Syntax** :: response = client.describe_notification_configurations( AutoScalingGroupNames=[ 'string', ], NextToken='string', MaxRecords=123 ) **Response Syntax** :: { 'NotificationConfigurations': [ { 'AutoScalingGroupName': 'string', 'TopicARN': 'string', 'NotificationType': 'string' }, ], 'NextToken': 'string' } **Response Structure** - *(dict) --* - **NotificationConfigurations** *(list) --* The notification configurations. - *(dict) --* Describes a notification. - **AutoScalingGroupName** *(string) --* The name of the Auto Scaling group. - **TopicARN** *(string) --* The Amazon Resource Name (ARN) of the Amazon Simple Notification Service (Amazon SNS) topic. - **NotificationType** *(string) --* One of the following event notification types: * ``autoscaling:EC2_INSTANCE_LAUNCH`` * ``autoscaling:EC2_INSTANCE_LAUNCH_ERROR`` * ``autoscaling:EC2_INSTANCE_TERMINATE`` * ``autoscaling:EC2_INSTANCE_TERMINATE_ERROR`` * ``autoscaling:TEST_NOTIFICATION`` - **NextToken** *(string) --* A string that indicates that the response contains more items than can be returned in a single response. To receive additional items, specify this string for the ``NextToken`` value when requesting the next set of items. This value is null when there are no more items to return. :type AutoScalingGroupNames: list :param AutoScalingGroupNames: The name of the Auto Scaling group. - *(string) --* :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :type MaxRecords: integer :param MaxRecords: The maximum number of items to return with this call. The default value is ``50`` and the maximum value is ``100`` . :rtype: dict :returns: """ pass def describe_policies(self, AutoScalingGroupName: str = None, PolicyNames: List = None, PolicyTypes: List = None, NextToken: str = None, MaxRecords: int = None) -> Dict: """ Describes the policies for the specified Auto Scaling group. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/DescribePolicies>`_ **Request Syntax** :: response = client.describe_policies( AutoScalingGroupName='string', PolicyNames=[ 'string', ], PolicyTypes=[ 'string', ], NextToken='string', MaxRecords=123 ) **Response Syntax** :: { 'ScalingPolicies': [ { 'AutoScalingGroupName': 'string', 'PolicyName': 'string', 'PolicyARN': 'string', 'PolicyType': 'string', 'AdjustmentType': 'string', 'MinAdjustmentStep': 123, 'MinAdjustmentMagnitude': 123, 'ScalingAdjustment': 123, 'Cooldown': 123, 'StepAdjustments': [ { 'MetricIntervalLowerBound': 123.0, 'MetricIntervalUpperBound': 123.0, 'ScalingAdjustment': 123 }, ], 'MetricAggregationType': 'string', 'EstimatedInstanceWarmup': 123, 'Alarms': [ { 'AlarmName': 'string', 'AlarmARN': 'string' }, ], 'TargetTrackingConfiguration': { 'PredefinedMetricSpecification': { 'PredefinedMetricType': 'ASGAverageCPUUtilization'|'ASGAverageNetworkIn'|'ASGAverageNetworkOut'|'ALBRequestCountPerTarget', 'ResourceLabel': 'string' }, 'CustomizedMetricSpecification': { 'MetricName': 'string', 'Namespace': 'string', 'Dimensions': [ { 'Name': 'string', 'Value': 'string' }, ], 'Statistic': 'Average'|'Minimum'|'Maximum'|'SampleCount'|'Sum', 'Unit': 'string' }, 'TargetValue': 123.0, 'DisableScaleIn': True|False } }, ], 'NextToken': 'string' } **Response Structure** - *(dict) --* - **ScalingPolicies** *(list) --* The scaling policies. - *(dict) --* Describes a scaling policy. - **AutoScalingGroupName** *(string) --* The name of the Auto Scaling group. - **PolicyName** *(string) --* The name of the scaling policy. - **PolicyARN** *(string) --* The Amazon Resource Name (ARN) of the policy. - **PolicyType** *(string) --* The policy type. The valid values are ``SimpleScaling`` and ``StepScaling`` . - **AdjustmentType** *(string) --* The adjustment type, which specifies how ``ScalingAdjustment`` is interpreted. The valid values are ``ChangeInCapacity`` , ``ExactCapacity`` , and ``PercentChangeInCapacity`` . - **MinAdjustmentStep** *(integer) --* Available for backward compatibility. Use ``MinAdjustmentMagnitude`` instead. - **MinAdjustmentMagnitude** *(integer) --* The minimum number of instances to scale. If the value of ``AdjustmentType`` is ``PercentChangeInCapacity`` , the scaling policy changes the ``DesiredCapacity`` of the Auto Scaling group by at least this many instances. Otherwise, the error is ``ValidationError`` . - **ScalingAdjustment** *(integer) --* The amount by which to scale, based on the specified adjustment type. A positive value adds to the current capacity while a negative number removes from the current capacity. - **Cooldown** *(integer) --* The amount of time, in seconds, after a scaling activity completes before any further dynamic scaling activities can start. - **StepAdjustments** *(list) --* A set of adjustments that enable you to scale based on the size of the alarm breach. - *(dict) --* Describes an adjustment based on the difference between the value of the aggregated CloudWatch metric and the breach threshold that you've defined for the alarm. Used in combination with PutScalingPolicy . For the following examples, suppose that you have an alarm with a breach threshold of 50: * To trigger the adjustment when the metric is greater than or equal to 50 and less than 60, specify a lower bound of 0 and an upper bound of 10. * To trigger the adjustment when the metric is greater than 40 and less than or equal to 50, specify a lower bound of -10 and an upper bound of 0. There are a few rules for the step adjustments for your step policy: * The ranges of your step adjustments can't overlap or have a gap. * At most, one step adjustment can have a null lower bound. If one step adjustment has a negative lower bound, then there must be a step adjustment with a null lower bound. * At most, one step adjustment can have a null upper bound. If one step adjustment has a positive upper bound, then there must be a step adjustment with a null upper bound. * The upper and lower bound can't be null in the same step adjustment. - **MetricIntervalLowerBound** *(float) --* The lower bound for the difference between the alarm threshold and the CloudWatch metric. If the metric value is above the breach threshold, the lower bound is inclusive (the metric must be greater than or equal to the threshold plus the lower bound). Otherwise, it is exclusive (the metric must be greater than the threshold plus the lower bound). A null value indicates negative infinity. - **MetricIntervalUpperBound** *(float) --* The upper bound for the difference between the alarm threshold and the CloudWatch metric. If the metric value is above the breach threshold, the upper bound is exclusive (the metric must be less than the threshold plus the upper bound). Otherwise, it is inclusive (the metric must be less than or equal to the threshold plus the upper bound). A null value indicates positive infinity. The upper bound must be greater than the lower bound. - **ScalingAdjustment** *(integer) --* The amount by which to scale, based on the specified adjustment type. A positive value adds to the current capacity while a negative number removes from the current capacity. - **MetricAggregationType** *(string) --* The aggregation type for the CloudWatch metrics. The valid values are ``Minimum`` , ``Maximum`` , and ``Average`` . - **EstimatedInstanceWarmup** *(integer) --* The estimated time, in seconds, until a newly launched instance can contribute to the CloudWatch metrics. - **Alarms** *(list) --* The CloudWatch alarms related to the policy. - *(dict) --* Describes an alarm. - **AlarmName** *(string) --* The name of the alarm. - **AlarmARN** *(string) --* The Amazon Resource Name (ARN) of the alarm. - **TargetTrackingConfiguration** *(dict) --* A target tracking scaling policy. - **PredefinedMetricSpecification** *(dict) --* A predefined metric. You can specify either a predefined metric or a customized metric. - **PredefinedMetricType** *(string) --* The metric type. - **ResourceLabel** *(string) --* Identifies the resource associated with the metric type. The following predefined metrics are available: * ``ASGAverageCPUUtilization`` - Average CPU utilization of the Auto Scaling group. * ``ASGAverageNetworkIn`` - Average number of bytes received on all network interfaces by the Auto Scaling group. * ``ASGAverageNetworkOut`` - Average number of bytes sent out on all network interfaces by the Auto Scaling group. * ``ALBRequestCountPerTarget`` - Number of requests completed per target in an Application Load Balancer or a Network Load Balancer target group. For predefined metric types ``ASGAverageCPUUtilization`` , ``ASGAverageNetworkIn`` , and ``ASGAverageNetworkOut`` , the parameter must not be specified as the resource associated with the metric type is the Auto Scaling group. For predefined metric type ``ALBRequestCountPerTarget`` , the parameter must be specified in the format: ``app/*load-balancer-name* /*load-balancer-id* /targetgroup/*target-group-name* /*target-group-id* `` , where ``app/*load-balancer-name* /*load-balancer-id* `` is the final portion of the load balancer ARN, and ``targetgroup/*target-group-name* /*target-group-id* `` is the final portion of the target group ARN. The target group must be attached to the Auto Scaling group. - **CustomizedMetricSpecification** *(dict) --* A customized metric. You can specify either a predefined metric or a customized metric. - **MetricName** *(string) --* The name of the metric. - **Namespace** *(string) --* The namespace of the metric. - **Dimensions** *(list) --* The dimensions of the metric. Conditional: If you published your metric with dimensions, you must specify the same dimensions in your scaling policy. - *(dict) --* Describes the dimension of a metric. - **Name** *(string) --* The name of the dimension. - **Value** *(string) --* The value of the dimension. - **Statistic** *(string) --* The statistic of the metric. - **Unit** *(string) --* The unit of the metric. - **TargetValue** *(float) --* The target value for the metric. - **DisableScaleIn** *(boolean) --* Indicates whether scaling in by the target tracking scaling policy is disabled. If scaling in is disabled, the target tracking scaling policy doesn't remove instances from the Auto Scaling group. Otherwise, the target tracking scaling policy can remove instances from the Auto Scaling group. The default is disabled. - **NextToken** *(string) --* A string that indicates that the response contains more items than can be returned in a single response. To receive additional items, specify this string for the ``NextToken`` value when requesting the next set of items. This value is null when there are no more items to return. :type AutoScalingGroupName: string :param AutoScalingGroupName: The name of the Auto Scaling group. :type PolicyNames: list :param PolicyNames: The names of one or more policies. If you omit this parameter, all policies are described. If a group name is provided, the results are limited to that group. This list is limited to 50 items. If you specify an unknown policy name, it is ignored with no error. - *(string) --* :type PolicyTypes: list :param PolicyTypes: One or more policy types. The valid values are ``SimpleScaling`` , ``StepScaling`` , and ``TargetTrackingScaling`` . - *(string) --* :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :type MaxRecords: integer :param MaxRecords: The maximum number of items to be returned with each call. The default value is ``50`` and the maximum value is ``100`` . :rtype: dict :returns: """ pass def describe_scaling_activities(self, ActivityIds: List = None, AutoScalingGroupName: str = None, MaxRecords: int = None, NextToken: str = None) -> Dict: """ Describes one or more scaling activities for the specified Auto Scaling group. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/DescribeScalingActivities>`_ **Request Syntax** :: response = client.describe_scaling_activities( ActivityIds=[ 'string', ], AutoScalingGroupName='string', MaxRecords=123, NextToken='string' ) **Response Syntax** :: { 'Activities': [ { 'ActivityId': 'string', 'AutoScalingGroupName': 'string', 'Description': 'string', 'Cause': 'string', 'StartTime': datetime(2015, 1, 1), 'EndTime': datetime(2015, 1, 1), 'StatusCode': 'PendingSpotBidPlacement'|'WaitingForSpotInstanceRequestId'|'WaitingForSpotInstanceId'|'WaitingForInstanceId'|'PreInService'|'InProgress'|'WaitingForELBConnectionDraining'|'MidLifecycleAction'|'WaitingForInstanceWarmup'|'Successful'|'Failed'|'Cancelled', 'StatusMessage': 'string', 'Progress': 123, 'Details': 'string' }, ], 'NextToken': 'string' } **Response Structure** - *(dict) --* - **Activities** *(list) --* The scaling activities. Activities are sorted by start time. Activities still in progress are described first. - *(dict) --* Describes scaling activity, which is a long-running process that represents a change to your Auto Scaling group, such as changing its size or replacing an instance. - **ActivityId** *(string) --* The ID of the activity. - **AutoScalingGroupName** *(string) --* The name of the Auto Scaling group. - **Description** *(string) --* A friendly, more verbose description of the activity. - **Cause** *(string) --* The reason the activity began. - **StartTime** *(datetime) --* The start time of the activity. - **EndTime** *(datetime) --* The end time of the activity. - **StatusCode** *(string) --* The current status of the activity. - **StatusMessage** *(string) --* A friendly, more verbose description of the activity status. - **Progress** *(integer) --* A value between 0 and 100 that indicates the progress of the activity. - **Details** *(string) --* The details about the activity. - **NextToken** *(string) --* A string that indicates that the response contains more items than can be returned in a single response. To receive additional items, specify this string for the ``NextToken`` value when requesting the next set of items. This value is null when there are no more items to return. :type ActivityIds: list :param ActivityIds: The activity IDs of the desired scaling activities. You can specify up to 50 IDs. If you omit this parameter, all activities for the past six weeks are described. If unknown activities are requested, they are ignored with no error. If you specify an Auto Scaling group, the results are limited to that group. - *(string) --* :type AutoScalingGroupName: string :param AutoScalingGroupName: The name of the Auto Scaling group. :type MaxRecords: integer :param MaxRecords: The maximum number of items to return with this call. The default value is ``100`` and the maximum value is ``100`` . :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :rtype: dict :returns: """ pass def describe_scaling_process_types(self) -> Dict: """ Describes the scaling process types for use with ResumeProcesses and SuspendProcesses . See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/DescribeScalingProcessTypes>`_ **Request Syntax** :: response = client.describe_scaling_process_types() **Response Syntax** :: { 'Processes': [ { 'ProcessName': 'string' }, ] } **Response Structure** - *(dict) --* - **Processes** *(list) --* The names of the process types. - *(dict) --* Describes a process type. For more information, see `Scaling Processes <https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-suspend-resume-processes.html#process-types>`__ in the *Amazon EC2 Auto Scaling User Guide* . - **ProcessName** *(string) --* One of the following processes: * ``Launch`` * ``Terminate`` * ``AddToLoadBalancer`` * ``AlarmNotification`` * ``AZRebalance`` * ``HealthCheck`` * ``ReplaceUnhealthy`` * ``ScheduledActions`` :rtype: dict :returns: """ pass def describe_scheduled_actions(self, AutoScalingGroupName: str = None, ScheduledActionNames: List = None, StartTime: datetime = None, EndTime: datetime = None, NextToken: str = None, MaxRecords: int = None) -> Dict: """ Describes the actions scheduled for your Auto Scaling group that haven't run. To describe the actions that have already run, use DescribeScalingActivities . See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/DescribeScheduledActions>`_ **Request Syntax** :: response = client.describe_scheduled_actions( AutoScalingGroupName='string', ScheduledActionNames=[ 'string', ], StartTime=datetime(2015, 1, 1), EndTime=datetime(2015, 1, 1), NextToken='string', MaxRecords=123 ) **Response Syntax** :: { 'ScheduledUpdateGroupActions': [ { 'AutoScalingGroupName': 'string', 'ScheduledActionName': 'string', 'ScheduledActionARN': 'string', 'Time': datetime(2015, 1, 1), 'StartTime': datetime(2015, 1, 1), 'EndTime': datetime(2015, 1, 1), 'Recurrence': 'string', 'MinSize': 123, 'MaxSize': 123, 'DesiredCapacity': 123 }, ], 'NextToken': 'string' } **Response Structure** - *(dict) --* - **ScheduledUpdateGroupActions** *(list) --* The scheduled actions. - *(dict) --* Describes a scheduled scaling action. Used in response to DescribeScheduledActions . - **AutoScalingGroupName** *(string) --* The name of the Auto Scaling group. - **ScheduledActionName** *(string) --* The name of the scheduled action. - **ScheduledActionARN** *(string) --* The Amazon Resource Name (ARN) of the scheduled action. - **Time** *(datetime) --* This parameter is deprecated. - **StartTime** *(datetime) --* The date and time that the action is scheduled to begin. When ``StartTime`` and ``EndTime`` are specified with ``Recurrence`` , they form the boundaries of when the recurring action starts and stops. - **EndTime** *(datetime) --* The date and time that the action is scheduled to end. - **Recurrence** *(string) --* The recurring schedule for the action. - **MinSize** *(integer) --* The minimum size of the group. - **MaxSize** *(integer) --* The maximum size of the group. - **DesiredCapacity** *(integer) --* The number of instances you prefer to maintain in the group. - **NextToken** *(string) --* A string that indicates that the response contains more items than can be returned in a single response. To receive additional items, specify this string for the ``NextToken`` value when requesting the next set of items. This value is null when there are no more items to return. :type AutoScalingGroupName: string :param AutoScalingGroupName: The name of the Auto Scaling group. :type ScheduledActionNames: list :param ScheduledActionNames: The names of one or more scheduled actions. You can specify up to 50 actions. If you omit this parameter, all scheduled actions are described. If you specify an unknown scheduled action, it is ignored with no error. - *(string) --* :type StartTime: datetime :param StartTime: The earliest scheduled start time to return. If scheduled action names are provided, this parameter is ignored. :type EndTime: datetime :param EndTime: The latest scheduled start time to return. If scheduled action names are provided, this parameter is ignored. :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :type MaxRecords: integer :param MaxRecords: The maximum number of items to return with this call. The default value is ``50`` and the maximum value is ``100`` . :rtype: dict :returns: """ pass def describe_tags(self, Filters: List = None, NextToken: str = None, MaxRecords: int = None) -> Dict: """ Describes the specified tags. You can use filters to limit the results. For example, you can query for the tags for a specific Auto Scaling group. You can specify multiple values for a filter. A tag must match at least one of the specified values for it to be included in the results. You can also specify multiple filters. The result includes information for a particular tag only if it matches all the filters. If there's no match, no special message is returned. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/DescribeTags>`_ **Request Syntax** :: response = client.describe_tags( Filters=[ { 'Name': 'string', 'Values': [ 'string', ] }, ], NextToken='string', MaxRecords=123 ) **Response Syntax** :: { 'Tags': [ { 'ResourceId': 'string', 'ResourceType': 'string', 'Key': 'string', 'Value': 'string', 'PropagateAtLaunch': True|False }, ], 'NextToken': 'string' } **Response Structure** - *(dict) --* - **Tags** *(list) --* One or more tags. - *(dict) --* Describes a tag for an Auto Scaling group. - **ResourceId** *(string) --* The name of the group. - **ResourceType** *(string) --* The type of resource. The only supported value is ``auto-scaling-group`` . - **Key** *(string) --* The tag key. - **Value** *(string) --* The tag value. - **PropagateAtLaunch** *(boolean) --* Determines whether the tag is added to new instances as they are launched in the group. - **NextToken** *(string) --* A string that indicates that the response contains more items than can be returned in a single response. To receive additional items, specify this string for the ``NextToken`` value when requesting the next set of items. This value is null when there are no more items to return. :type Filters: list :param Filters: One or more filters to scope the tags to return. The maximum number of filters per filter type (for example, ``auto-scaling-group`` ) is 1000. - *(dict) --* Describes a filter. - **Name** *(string) --* The name of the filter. The valid values are: ``\"auto-scaling-group\"`` , ``\"key\"`` , ``\"value\"`` , and ``\"propagate-at-launch\"`` . - **Values** *(list) --* The value of the filter. - *(string) --* :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :type MaxRecords: integer :param MaxRecords: The maximum number of items to return with this call. The default value is ``50`` and the maximum value is ``100`` . :rtype: dict :returns: """ pass def describe_termination_policy_types(self) -> Dict: """ Describes the termination policies supported by Amazon EC2 Auto Scaling. For more information, see `Controlling Which Auto Scaling Instances Terminate During Scale In <https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-instance-termination.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/DescribeTerminationPolicyTypes>`_ **Request Syntax** :: response = client.describe_termination_policy_types() **Response Syntax** :: { 'TerminationPolicyTypes': [ 'string', ] } **Response Structure** - *(dict) --* - **TerminationPolicyTypes** *(list) --* The termination policies supported by Amazon EC2 Auto Scaling: ``OldestInstance`` , ``OldestLaunchConfiguration`` , ``NewestInstance`` , ``ClosestToNextInstanceHour`` , ``Default`` , ``OldestLaunchTemplate`` , and ``AllocationStrategy`` . - *(string) --* :rtype: dict :returns: """ pass def detach_instances(self, AutoScalingGroupName: str, ShouldDecrementDesiredCapacity: bool, InstanceIds: List = None) -> Dict: """ Removes one or more instances from the specified Auto Scaling group. After the instances are detached, you can manage them independent of the Auto Scaling group. If you do not specify the option to decrement the desired capacity, Amazon EC2 Auto Scaling launches instances to replace the ones that are detached. If there is a Classic Load Balancer attached to the Auto Scaling group, the instances are deregistered from the load balancer. If there are target groups attached to the Auto Scaling group, the instances are deregistered from the target groups. For more information, see `Detach EC2 Instances from Your Auto Scaling Group <https://docs.aws.amazon.com/autoscaling/ec2/userguide/detach-instance-asg.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/DetachInstances>`_ **Request Syntax** :: response = client.detach_instances( InstanceIds=[ 'string', ], AutoScalingGroupName='string', ShouldDecrementDesiredCapacity=True|False ) **Response Syntax** :: { 'Activities': [ { 'ActivityId': 'string', 'AutoScalingGroupName': 'string', 'Description': 'string', 'Cause': 'string', 'StartTime': datetime(2015, 1, 1), 'EndTime': datetime(2015, 1, 1), 'StatusCode': 'PendingSpotBidPlacement'|'WaitingForSpotInstanceRequestId'|'WaitingForSpotInstanceId'|'WaitingForInstanceId'|'PreInService'|'InProgress'|'WaitingForELBConnectionDraining'|'MidLifecycleAction'|'WaitingForInstanceWarmup'|'Successful'|'Failed'|'Cancelled', 'StatusMessage': 'string', 'Progress': 123, 'Details': 'string' }, ] } **Response Structure** - *(dict) --* - **Activities** *(list) --* The activities related to detaching the instances from the Auto Scaling group. - *(dict) --* Describes scaling activity, which is a long-running process that represents a change to your Auto Scaling group, such as changing its size or replacing an instance. - **ActivityId** *(string) --* The ID of the activity. - **AutoScalingGroupName** *(string) --* The name of the Auto Scaling group. - **Description** *(string) --* A friendly, more verbose description of the activity. - **Cause** *(string) --* The reason the activity began. - **StartTime** *(datetime) --* The start time of the activity. - **EndTime** *(datetime) --* The end time of the activity. - **StatusCode** *(string) --* The current status of the activity. - **StatusMessage** *(string) --* A friendly, more verbose description of the activity status. - **Progress** *(integer) --* A value between 0 and 100 that indicates the progress of the activity. - **Details** *(string) --* The details about the activity. :type InstanceIds: list :param InstanceIds: The IDs of the instances. You can specify up to 20 instances. - *(string) --* :type AutoScalingGroupName: string :param AutoScalingGroupName: **[REQUIRED]** The name of the Auto Scaling group. :type ShouldDecrementDesiredCapacity: boolean :param ShouldDecrementDesiredCapacity: **[REQUIRED]** Indicates whether the Auto Scaling group decrements the desired capacity value by the number of instances detached. :rtype: dict :returns: """ pass def detach_load_balancer_target_groups(self, AutoScalingGroupName: str, TargetGroupARNs: List) -> Dict: """ Detaches one or more target groups from the specified Auto Scaling group. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/DetachLoadBalancerTargetGroups>`_ **Request Syntax** :: response = client.detach_load_balancer_target_groups( AutoScalingGroupName='string', TargetGroupARNs=[ 'string', ] ) **Response Syntax** :: {} **Response Structure** - *(dict) --* :type AutoScalingGroupName: string :param AutoScalingGroupName: **[REQUIRED]** The name of the Auto Scaling group. :type TargetGroupARNs: list :param TargetGroupARNs: **[REQUIRED]** The Amazon Resource Names (ARN) of the target groups. You can specify up to 10 target groups. - *(string) --* :rtype: dict :returns: """ pass def detach_load_balancers(self, AutoScalingGroupName: str, LoadBalancerNames: List) -> Dict: """ Detaches one or more Classic Load Balancers from the specified Auto Scaling group. This operation detaches only Classic Load Balancers. If you have Application Load Balancers or Network Load Balancers, use DetachLoadBalancerTargetGroups instead. When you detach a load balancer, it enters the ``Removing`` state while deregistering the instances in the group. When all instances are deregistered, then you can no longer describe the load balancer using DescribeLoadBalancers . The instances remain running. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/DetachLoadBalancers>`_ **Request Syntax** :: response = client.detach_load_balancers( AutoScalingGroupName='string', LoadBalancerNames=[ 'string', ] ) **Response Syntax** :: {} **Response Structure** - *(dict) --* :type AutoScalingGroupName: string :param AutoScalingGroupName: **[REQUIRED]** The name of the Auto Scaling group. :type LoadBalancerNames: list :param LoadBalancerNames: **[REQUIRED]** The names of the load balancers. You can specify up to 10 load balancers. - *(string) --* :rtype: dict :returns: """ pass def disable_metrics_collection(self, AutoScalingGroupName: str, Metrics: List = None): """ Disables group metrics for the specified Auto Scaling group. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/DisableMetricsCollection>`_ **Request Syntax** :: response = client.disable_metrics_collection( AutoScalingGroupName='string', Metrics=[ 'string', ] ) :type AutoScalingGroupName: string :param AutoScalingGroupName: **[REQUIRED]** The name of the Auto Scaling group. :type Metrics: list :param Metrics: One or more of the following metrics. If you omit this parameter, all metrics are disabled. * ``GroupMinSize`` * ``GroupMaxSize`` * ``GroupDesiredCapacity`` * ``GroupInServiceInstances`` * ``GroupPendingInstances`` * ``GroupStandbyInstances`` * ``GroupTerminatingInstances`` * ``GroupTotalInstances`` - *(string) --* :returns: None """ pass def enable_metrics_collection(self, AutoScalingGroupName: str, Granularity: str, Metrics: List = None): """ Enables group metrics for the specified Auto Scaling group. For more information, see `Monitoring Your Auto Scaling Groups and Instances <https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-instance-monitoring.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/EnableMetricsCollection>`_ **Request Syntax** :: response = client.enable_metrics_collection( AutoScalingGroupName='string', Metrics=[ 'string', ], Granularity='string' ) :type AutoScalingGroupName: string :param AutoScalingGroupName: **[REQUIRED]** The name of the Auto Scaling group. :type Metrics: list :param Metrics: One or more of the following metrics. If you omit this parameter, all metrics are enabled. * ``GroupMinSize`` * ``GroupMaxSize`` * ``GroupDesiredCapacity`` * ``GroupInServiceInstances`` * ``GroupPendingInstances`` * ``GroupStandbyInstances`` * ``GroupTerminatingInstances`` * ``GroupTotalInstances`` - *(string) --* :type Granularity: string :param Granularity: **[REQUIRED]** The granularity to associate with the metrics to collect. The only valid value is ``1Minute`` . :returns: None """ pass def enter_standby(self, AutoScalingGroupName: str, ShouldDecrementDesiredCapacity: bool, InstanceIds: List = None) -> Dict: """ Moves the specified instances into the standby state. For more information, see `Temporarily Removing Instances from Your Auto Scaling Group <https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-enter-exit-standby.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/EnterStandby>`_ **Request Syntax** :: response = client.enter_standby( InstanceIds=[ 'string', ], AutoScalingGroupName='string', ShouldDecrementDesiredCapacity=True|False ) **Response Syntax** :: { 'Activities': [ { 'ActivityId': 'string', 'AutoScalingGroupName': 'string', 'Description': 'string', 'Cause': 'string', 'StartTime': datetime(2015, 1, 1), 'EndTime': datetime(2015, 1, 1), 'StatusCode': 'PendingSpotBidPlacement'|'WaitingForSpotInstanceRequestId'|'WaitingForSpotInstanceId'|'WaitingForInstanceId'|'PreInService'|'InProgress'|'WaitingForELBConnectionDraining'|'MidLifecycleAction'|'WaitingForInstanceWarmup'|'Successful'|'Failed'|'Cancelled', 'StatusMessage': 'string', 'Progress': 123, 'Details': 'string' }, ] } **Response Structure** - *(dict) --* - **Activities** *(list) --* The activities related to moving instances into ``Standby`` mode. - *(dict) --* Describes scaling activity, which is a long-running process that represents a change to your Auto Scaling group, such as changing its size or replacing an instance. - **ActivityId** *(string) --* The ID of the activity. - **AutoScalingGroupName** *(string) --* The name of the Auto Scaling group. - **Description** *(string) --* A friendly, more verbose description of the activity. - **Cause** *(string) --* The reason the activity began. - **StartTime** *(datetime) --* The start time of the activity. - **EndTime** *(datetime) --* The end time of the activity. - **StatusCode** *(string) --* The current status of the activity. - **StatusMessage** *(string) --* A friendly, more verbose description of the activity status. - **Progress** *(integer) --* A value between 0 and 100 that indicates the progress of the activity. - **Details** *(string) --* The details about the activity. :type InstanceIds: list :param InstanceIds: The IDs of the instances. You can specify up to 20 instances. - *(string) --* :type AutoScalingGroupName: string :param AutoScalingGroupName: **[REQUIRED]** The name of the Auto Scaling group. :type ShouldDecrementDesiredCapacity: boolean :param ShouldDecrementDesiredCapacity: **[REQUIRED]** Indicates whether to decrement the desired capacity of the Auto Scaling group by the number of instances moved to ``Standby`` mode. :rtype: dict :returns: """ pass def execute_policy(self, PolicyName: str, AutoScalingGroupName: str = None, HonorCooldown: bool = None, MetricValue: float = None, BreachThreshold: float = None): """ Executes the specified policy. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/ExecutePolicy>`_ **Request Syntax** :: response = client.execute_policy( AutoScalingGroupName='string', PolicyName='string', HonorCooldown=True|False, MetricValue=123.0, BreachThreshold=123.0 ) :type AutoScalingGroupName: string :param AutoScalingGroupName: The name of the Auto Scaling group. :type PolicyName: string :param PolicyName: **[REQUIRED]** The name or ARN of the policy. :type HonorCooldown: boolean :param HonorCooldown: Indicates whether Amazon EC2 Auto Scaling waits for the cooldown period to complete before executing the policy. This parameter is not supported if the policy type is ``StepScaling`` . For more information, see `Scaling Cooldowns <https://docs.aws.amazon.com/autoscaling/ec2/userguide/Cooldown.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . :type MetricValue: float :param MetricValue: The metric value to compare to ``BreachThreshold`` . This enables you to execute a policy of type ``StepScaling`` and determine which step adjustment to use. For example, if the breach threshold is 50 and you want to use a step adjustment with a lower bound of 0 and an upper bound of 10, you can set the metric value to 59. If you specify a metric value that doesn\'t correspond to a step adjustment for the policy, the call returns an error. Conditional: This parameter is required if the policy type is ``StepScaling`` and not supported otherwise. :type BreachThreshold: float :param BreachThreshold: The breach threshold for the alarm. Conditional: This parameter is required if the policy type is ``StepScaling`` and not supported otherwise. :returns: None """ pass def exit_standby(self, AutoScalingGroupName: str, InstanceIds: List = None) -> Dict: """ Moves the specified instances out of the standby state. For more information, see `Temporarily Removing Instances from Your Auto Scaling Group <https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-enter-exit-standby.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/ExitStandby>`_ **Request Syntax** :: response = client.exit_standby( InstanceIds=[ 'string', ], AutoScalingGroupName='string' ) **Response Syntax** :: { 'Activities': [ { 'ActivityId': 'string', 'AutoScalingGroupName': 'string', 'Description': 'string', 'Cause': 'string', 'StartTime': datetime(2015, 1, 1), 'EndTime': datetime(2015, 1, 1), 'StatusCode': 'PendingSpotBidPlacement'|'WaitingForSpotInstanceRequestId'|'WaitingForSpotInstanceId'|'WaitingForInstanceId'|'PreInService'|'InProgress'|'WaitingForELBConnectionDraining'|'MidLifecycleAction'|'WaitingForInstanceWarmup'|'Successful'|'Failed'|'Cancelled', 'StatusMessage': 'string', 'Progress': 123, 'Details': 'string' }, ] } **Response Structure** - *(dict) --* - **Activities** *(list) --* The activities related to moving instances out of ``Standby`` mode. - *(dict) --* Describes scaling activity, which is a long-running process that represents a change to your Auto Scaling group, such as changing its size or replacing an instance. - **ActivityId** *(string) --* The ID of the activity. - **AutoScalingGroupName** *(string) --* The name of the Auto Scaling group. - **Description** *(string) --* A friendly, more verbose description of the activity. - **Cause** *(string) --* The reason the activity began. - **StartTime** *(datetime) --* The start time of the activity. - **EndTime** *(datetime) --* The end time of the activity. - **StatusCode** *(string) --* The current status of the activity. - **StatusMessage** *(string) --* A friendly, more verbose description of the activity status. - **Progress** *(integer) --* A value between 0 and 100 that indicates the progress of the activity. - **Details** *(string) --* The details about the activity. :type InstanceIds: list :param InstanceIds: The IDs of the instances. You can specify up to 20 instances. - *(string) --* :type AutoScalingGroupName: string :param AutoScalingGroupName: **[REQUIRED]** The name of the Auto Scaling group. :rtype: dict :returns: """ pass def generate_presigned_url(self, ClientMethod: str = None, Params: Dict = None, ExpiresIn: int = None, HttpMethod: str = None): """ Generate a presigned url given a client, its method, and arguments :type ClientMethod: string :param ClientMethod: The client method to presign for :type Params: dict :param Params: The parameters normally passed to ``ClientMethod``. :type ExpiresIn: int :param ExpiresIn: The number of seconds the presigned url is valid for. By default it expires in an hour (3600 seconds) :type HttpMethod: string :param HttpMethod: The http method to use on the generated url. By default, the http method is whatever is used in the method\'s model. :returns: The presigned url """ pass def get_paginator(self, operation_name: str = None) -> Paginator: """ Create a paginator for an operation. :type operation_name: string :param operation_name: The operation name. This is the same name as the method name on the client. For example, if the method name is ``create_foo``, and you\'d normally invoke the operation as ``client.create_foo(**kwargs)``, if the ``create_foo`` operation can be paginated, you can use the call ``client.get_paginator(\"create_foo\")``. :raise OperationNotPageableError: Raised if the operation is not pageable. You can use the ``client.can_paginate`` method to check if an operation is pageable. :rtype: L{botocore.paginate.Paginator} :return: A paginator object. """ pass def get_waiter(self, waiter_name: str = None) -> Waiter: """ Returns an object that can wait for some condition. :type waiter_name: str :param waiter_name: The name of the waiter to get. See the waiters section of the service docs for a list of available waiters. :returns: The specified waiter object. :rtype: botocore.waiter.Waiter """ pass def put_lifecycle_hook(self, LifecycleHookName: str, AutoScalingGroupName: str, LifecycleTransition: str = None, RoleARN: str = None, NotificationTargetARN: str = None, NotificationMetadata: str = None, HeartbeatTimeout: int = None, DefaultResult: str = None) -> Dict: """ Creates or updates a lifecycle hook for the specified Auto Scaling group. A lifecycle hook tells Amazon EC2 Auto Scaling to perform an action on an instance when the instance launches (before it is put into service) or as the instance terminates (before it is fully terminated). This step is a part of the procedure for adding a lifecycle hook to an Auto Scaling group: * (Optional) Create a Lambda function and a rule that allows CloudWatch Events to invoke your Lambda function when Amazon EC2 Auto Scaling launches or terminates instances. * (Optional) Create a notification target and an IAM role. The target can be either an Amazon SQS queue or an Amazon SNS topic. The role allows Amazon EC2 Auto Scaling to publish lifecycle notifications to the target. * **Create the lifecycle hook. Specify whether the hook is used when the instances launch or terminate.** * If you need more time, record the lifecycle action heartbeat to keep the instance in a pending state using using RecordLifecycleActionHeartbeat . * If you finish before the timeout period ends, complete the lifecycle action using CompleteLifecycleAction . For more information, see `Amazon EC2 Auto Scaling Lifecycle Hooks <https://docs.aws.amazon.com/autoscaling/ec2/userguide/lifecycle-hooks.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . If you exceed your maximum limit of lifecycle hooks, which by default is 50 per Auto Scaling group, the call fails. You can view the lifecycle hooks for an Auto Scaling group using DescribeLifecycleHooks . If you are no longer using a lifecycle hook, you can delete it using DeleteLifecycleHook . See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/PutLifecycleHook>`_ **Request Syntax** :: response = client.put_lifecycle_hook( LifecycleHookName='string', AutoScalingGroupName='string', LifecycleTransition='string', RoleARN='string', NotificationTargetARN='string', NotificationMetadata='string', HeartbeatTimeout=123, DefaultResult='string' ) **Response Syntax** :: {} **Response Structure** - *(dict) --* :type LifecycleHookName: string :param LifecycleHookName: **[REQUIRED]** The name of the lifecycle hook. :type AutoScalingGroupName: string :param AutoScalingGroupName: **[REQUIRED]** The name of the Auto Scaling group. :type LifecycleTransition: string :param LifecycleTransition: The instance state to which you want to attach the lifecycle hook. The valid values are: * autoscaling:EC2_INSTANCE_LAUNCHING * autoscaling:EC2_INSTANCE_TERMINATING Conditional: This parameter is required for new lifecycle hooks, but optional when updating existing hooks. :type RoleARN: string :param RoleARN: The ARN of the IAM role that allows the Auto Scaling group to publish to the specified notification target, for example, an Amazon SNS topic or an Amazon SQS queue. Conditional: This parameter is required for new lifecycle hooks, but optional when updating existing hooks. :type NotificationTargetARN: string :param NotificationTargetARN: The ARN of the notification target that Amazon EC2 Auto Scaling uses to notify you when an instance is in the transition state for the lifecycle hook. This target can be either an SQS queue or an SNS topic. If you specify an empty string, this overrides the current ARN. This operation uses the JSON format when sending notifications to an Amazon SQS queue, and an email key-value pair format when sending notifications to an Amazon SNS topic. When you specify a notification target, Amazon EC2 Auto Scaling sends it a test message. Test messages contain the following additional key-value pair: ``\"Event\": \"autoscaling:TEST_NOTIFICATION\"`` . :type NotificationMetadata: string :param NotificationMetadata: Additional information that you want to include any time Amazon EC2 Auto Scaling sends a message to the notification target. :type HeartbeatTimeout: integer :param HeartbeatTimeout: The maximum time, in seconds, that can elapse before the lifecycle hook times out. The range is from ``30`` to ``7200`` seconds. The default value is ``3600`` seconds (1 hour). If the lifecycle hook times out, Amazon EC2 Auto Scaling performs the action that you specified in the ``DefaultResult`` parameter. You can prevent the lifecycle hook from timing out by calling RecordLifecycleActionHeartbeat . :type DefaultResult: string :param DefaultResult: Defines the action the Auto Scaling group should take when the lifecycle hook timeout elapses or if an unexpected failure occurs. This parameter can be either ``CONTINUE`` or ``ABANDON`` . The default value is ``ABANDON`` . :rtype: dict :returns: """ pass def put_notification_configuration(self, AutoScalingGroupName: str, TopicARN: str, NotificationTypes: List): """ Configures an Auto Scaling group to send notifications when specified events take place. Subscribers to the specified topic can have messages delivered to an endpoint such as a web server or an email address. This configuration overwrites any existing configuration. For more information, see `Getting Amazon SNS Notifications When Your Auto Scaling Group Scales <https://docs.aws.amazon.com/autoscaling/ec2/userguide/ASGettingNotifications.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/PutNotificationConfiguration>`_ **Request Syntax** :: response = client.put_notification_configuration( AutoScalingGroupName='string', TopicARN='string', NotificationTypes=[ 'string', ] ) :type AutoScalingGroupName: string :param AutoScalingGroupName: **[REQUIRED]** The name of the Auto Scaling group. :type TopicARN: string :param TopicARN: **[REQUIRED]** The Amazon Resource Name (ARN) of the Amazon Simple Notification Service (Amazon SNS) topic. :type NotificationTypes: list :param NotificationTypes: **[REQUIRED]** The type of event that causes the notification to be sent. For more information about notification types supported by Amazon EC2 Auto Scaling, see DescribeAutoScalingNotificationTypes . - *(string) --* :returns: None """ pass def put_scaling_policy(self, AutoScalingGroupName: str, PolicyName: str, PolicyType: str = None, AdjustmentType: str = None, MinAdjustmentStep: int = None, MinAdjustmentMagnitude: int = None, ScalingAdjustment: int = None, Cooldown: int = None, MetricAggregationType: str = None, StepAdjustments: List = None, EstimatedInstanceWarmup: int = None, TargetTrackingConfiguration: Dict = None) -> Dict: """ Creates or updates a policy for an Auto Scaling group. To update an existing policy, use the existing policy name and set the parameters to change. Any existing parameter not changed in an update to an existing policy is not changed in this update request. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/PutScalingPolicy>`_ **Request Syntax** :: response = client.put_scaling_policy( AutoScalingGroupName='string', PolicyName='string', PolicyType='string', AdjustmentType='string', MinAdjustmentStep=123, MinAdjustmentMagnitude=123, ScalingAdjustment=123, Cooldown=123, MetricAggregationType='string', StepAdjustments=[ { 'MetricIntervalLowerBound': 123.0, 'MetricIntervalUpperBound': 123.0, 'ScalingAdjustment': 123 }, ], EstimatedInstanceWarmup=123, TargetTrackingConfiguration={ 'PredefinedMetricSpecification': { 'PredefinedMetricType': 'ASGAverageCPUUtilization'|'ASGAverageNetworkIn'|'ASGAverageNetworkOut'|'ALBRequestCountPerTarget', 'ResourceLabel': 'string' }, 'CustomizedMetricSpecification': { 'MetricName': 'string', 'Namespace': 'string', 'Dimensions': [ { 'Name': 'string', 'Value': 'string' }, ], 'Statistic': 'Average'|'Minimum'|'Maximum'|'SampleCount'|'Sum', 'Unit': 'string' }, 'TargetValue': 123.0, 'DisableScaleIn': True|False } ) **Response Syntax** :: { 'PolicyARN': 'string', 'Alarms': [ { 'AlarmName': 'string', 'AlarmARN': 'string' }, ] } **Response Structure** - *(dict) --* Contains the output of PutScalingPolicy. - **PolicyARN** *(string) --* The Amazon Resource Name (ARN) of the policy. - **Alarms** *(list) --* The CloudWatch alarms created for the target tracking scaling policy. - *(dict) --* Describes an alarm. - **AlarmName** *(string) --* The name of the alarm. - **AlarmARN** *(string) --* The Amazon Resource Name (ARN) of the alarm. :type AutoScalingGroupName: string :param AutoScalingGroupName: **[REQUIRED]** The name of the Auto Scaling group. :type PolicyName: string :param PolicyName: **[REQUIRED]** The name of the policy. :type PolicyType: string :param PolicyType: The policy type. The valid values are ``SimpleScaling`` , ``StepScaling`` , and ``TargetTrackingScaling`` . If the policy type is null, the value is treated as ``SimpleScaling`` . :type AdjustmentType: string :param AdjustmentType: The adjustment type. The valid values are ``ChangeInCapacity`` , ``ExactCapacity`` , and ``PercentChangeInCapacity`` . This parameter is supported if the policy type is ``SimpleScaling`` or ``StepScaling`` . For more information, see `Dynamic Scaling <https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-scale-based-on-demand.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . :type MinAdjustmentStep: integer :param MinAdjustmentStep: Available for backward compatibility. Use ``MinAdjustmentMagnitude`` instead. :type MinAdjustmentMagnitude: integer :param MinAdjustmentMagnitude: The minimum number of instances to scale. If the value of ``AdjustmentType`` is ``PercentChangeInCapacity`` , the scaling policy changes the ``DesiredCapacity`` of the Auto Scaling group by at least this many instances. Otherwise, the error is ``ValidationError`` . This parameter is supported if the policy type is ``SimpleScaling`` or ``StepScaling`` . :type ScalingAdjustment: integer :param ScalingAdjustment: The amount by which to scale, based on the specified adjustment type. A positive value adds to the current capacity while a negative number removes from the current capacity. Conditional: This parameter is required if the policy type is ``SimpleScaling`` and not supported otherwise. :type Cooldown: integer :param Cooldown: The amount of time, in seconds, after a scaling activity completes and before the next scaling activity can start. If this parameter is not specified, the default cooldown period for the group applies. This parameter is supported if the policy type is ``SimpleScaling`` . For more information, see `Scaling Cooldowns <https://docs.aws.amazon.com/autoscaling/ec2/userguide/Cooldown.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . :type MetricAggregationType: string :param MetricAggregationType: The aggregation type for the CloudWatch metrics. The valid values are ``Minimum`` , ``Maximum`` , and ``Average`` . If the aggregation type is null, the value is treated as ``Average`` . This parameter is supported if the policy type is ``StepScaling`` . :type StepAdjustments: list :param StepAdjustments: A set of adjustments that enable you to scale based on the size of the alarm breach. Conditional: This parameter is required if the policy type is ``StepScaling`` and not supported otherwise. - *(dict) --* Describes an adjustment based on the difference between the value of the aggregated CloudWatch metric and the breach threshold that you\'ve defined for the alarm. Used in combination with PutScalingPolicy . For the following examples, suppose that you have an alarm with a breach threshold of 50: * To trigger the adjustment when the metric is greater than or equal to 50 and less than 60, specify a lower bound of 0 and an upper bound of 10. * To trigger the adjustment when the metric is greater than 40 and less than or equal to 50, specify a lower bound of -10 and an upper bound of 0. There are a few rules for the step adjustments for your step policy: * The ranges of your step adjustments can\'t overlap or have a gap. * At most, one step adjustment can have a null lower bound. If one step adjustment has a negative lower bound, then there must be a step adjustment with a null lower bound. * At most, one step adjustment can have a null upper bound. If one step adjustment has a positive upper bound, then there must be a step adjustment with a null upper bound. * The upper and lower bound can\'t be null in the same step adjustment. - **MetricIntervalLowerBound** *(float) --* The lower bound for the difference between the alarm threshold and the CloudWatch metric. If the metric value is above the breach threshold, the lower bound is inclusive (the metric must be greater than or equal to the threshold plus the lower bound). Otherwise, it is exclusive (the metric must be greater than the threshold plus the lower bound). A null value indicates negative infinity. - **MetricIntervalUpperBound** *(float) --* The upper bound for the difference between the alarm threshold and the CloudWatch metric. If the metric value is above the breach threshold, the upper bound is exclusive (the metric must be less than the threshold plus the upper bound). Otherwise, it is inclusive (the metric must be less than or equal to the threshold plus the upper bound). A null value indicates positive infinity. The upper bound must be greater than the lower bound. - **ScalingAdjustment** *(integer) --* **[REQUIRED]** The amount by which to scale, based on the specified adjustment type. A positive value adds to the current capacity while a negative number removes from the current capacity. :type EstimatedInstanceWarmup: integer :param EstimatedInstanceWarmup: The estimated time, in seconds, until a newly launched instance can contribute to the CloudWatch metrics. The default is to use the value specified for the default cooldown period for the group. This parameter is supported if the policy type is ``StepScaling`` or ``TargetTrackingScaling`` . :type TargetTrackingConfiguration: dict :param TargetTrackingConfiguration: A target tracking scaling policy. Includes support for predefined or customized metrics. Conditional: This parameter is required if the policy type is ``TargetTrackingScaling`` and not supported otherwise. - **PredefinedMetricSpecification** *(dict) --* A predefined metric. You can specify either a predefined metric or a customized metric. - **PredefinedMetricType** *(string) --* **[REQUIRED]** The metric type. - **ResourceLabel** *(string) --* Identifies the resource associated with the metric type. The following predefined metrics are available: * ``ASGAverageCPUUtilization`` - Average CPU utilization of the Auto Scaling group. * ``ASGAverageNetworkIn`` - Average number of bytes received on all network interfaces by the Auto Scaling group. * ``ASGAverageNetworkOut`` - Average number of bytes sent out on all network interfaces by the Auto Scaling group. * ``ALBRequestCountPerTarget`` - Number of requests completed per target in an Application Load Balancer or a Network Load Balancer target group. For predefined metric types ``ASGAverageCPUUtilization`` , ``ASGAverageNetworkIn`` , and ``ASGAverageNetworkOut`` , the parameter must not be specified as the resource associated with the metric type is the Auto Scaling group. For predefined metric type ``ALBRequestCountPerTarget`` , the parameter must be specified in the format: ``app/*load-balancer-name* /*load-balancer-id* /targetgroup/*target-group-name* /*target-group-id* `` , where ``app/*load-balancer-name* /*load-balancer-id* `` is the final portion of the load balancer ARN, and ``targetgroup/*target-group-name* /*target-group-id* `` is the final portion of the target group ARN. The target group must be attached to the Auto Scaling group. - **CustomizedMetricSpecification** *(dict) --* A customized metric. You can specify either a predefined metric or a customized metric. - **MetricName** *(string) --* **[REQUIRED]** The name of the metric. - **Namespace** *(string) --* **[REQUIRED]** The namespace of the metric. - **Dimensions** *(list) --* The dimensions of the metric. Conditional: If you published your metric with dimensions, you must specify the same dimensions in your scaling policy. - *(dict) --* Describes the dimension of a metric. - **Name** *(string) --* **[REQUIRED]** The name of the dimension. - **Value** *(string) --* **[REQUIRED]** The value of the dimension. - **Statistic** *(string) --* **[REQUIRED]** The statistic of the metric. - **Unit** *(string) --* The unit of the metric. - **TargetValue** *(float) --* **[REQUIRED]** The target value for the metric. - **DisableScaleIn** *(boolean) --* Indicates whether scaling in by the target tracking scaling policy is disabled. If scaling in is disabled, the target tracking scaling policy doesn\'t remove instances from the Auto Scaling group. Otherwise, the target tracking scaling policy can remove instances from the Auto Scaling group. The default is disabled. :rtype: dict :returns: """ pass def put_scheduled_update_group_action(self, AutoScalingGroupName: str, ScheduledActionName: str, Time: datetime = None, StartTime: datetime = None, EndTime: datetime = None, Recurrence: str = None, MinSize: int = None, MaxSize: int = None, DesiredCapacity: int = None): """ Creates or updates a scheduled scaling action for an Auto Scaling group. If you leave a parameter unspecified when updating a scheduled scaling action, the corresponding value remains unchanged. For more information, see `Scheduled Scaling <https://docs.aws.amazon.com/autoscaling/ec2/userguide/schedule_time.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/PutScheduledUpdateGroupAction>`_ **Request Syntax** :: response = client.put_scheduled_update_group_action( AutoScalingGroupName='string', ScheduledActionName='string', Time=datetime(2015, 1, 1), StartTime=datetime(2015, 1, 1), EndTime=datetime(2015, 1, 1), Recurrence='string', MinSize=123, MaxSize=123, DesiredCapacity=123 ) :type AutoScalingGroupName: string :param AutoScalingGroupName: **[REQUIRED]** The name of the Auto Scaling group. :type ScheduledActionName: string :param ScheduledActionName: **[REQUIRED]** The name of this scaling action. :type Time: datetime :param Time: This parameter is deprecated. :type StartTime: datetime :param StartTime: The time for this action to start, in YYYY-MM-DDThh:mm:ssZ format in UTC/GMT only and in quotes (for example, ``\"2019-06-01T00:00:00Z\"`` ). If you specify ``Recurrence`` and ``StartTime`` , Amazon EC2 Auto Scaling performs the action at this time, and then performs the action based on the specified recurrence. If you try to schedule your action in the past, Amazon EC2 Auto Scaling returns an error message. :type EndTime: datetime :param EndTime: The time for the recurring schedule to end. Amazon EC2 Auto Scaling does not perform the action after this time. :type Recurrence: string :param Recurrence: The recurring schedule for this action, in Unix cron syntax format. This format consists of five fields separated by white spaces: [Minute] [Hour] [Day_of_Month] [Month_of_Year] [Day_of_Week]. The value must be in quotes (for example, ``\"30 0 1 1,6,12 *\"`` ). For more information about this format, see `Crontab <http://crontab.org>`__ . :type MinSize: integer :param MinSize: The minimum size for the Auto Scaling group. :type MaxSize: integer :param MaxSize: The maximum size for the Auto Scaling group. :type DesiredCapacity: integer :param DesiredCapacity: The number of EC2 instances that should be running in the group. :returns: None """ pass def record_lifecycle_action_heartbeat(self, LifecycleHookName: str, AutoScalingGroupName: str, LifecycleActionToken: str = None, InstanceId: str = None) -> Dict: """ Records a heartbeat for the lifecycle action associated with the specified token or instance. This extends the timeout by the length of time defined using PutLifecycleHook . This step is a part of the procedure for adding a lifecycle hook to an Auto Scaling group: * (Optional) Create a Lambda function and a rule that allows CloudWatch Events to invoke your Lambda function when Amazon EC2 Auto Scaling launches or terminates instances. * (Optional) Create a notification target and an IAM role. The target can be either an Amazon SQS queue or an Amazon SNS topic. The role allows Amazon EC2 Auto Scaling to publish lifecycle notifications to the target. * Create the lifecycle hook. Specify whether the hook is used when the instances launch or terminate. * **If you need more time, record the lifecycle action heartbeat to keep the instance in a pending state.** * If you finish before the timeout period ends, complete the lifecycle action. For more information, see `Auto Scaling Lifecycle <https://docs.aws.amazon.com/autoscaling/ec2/userguide/AutoScalingGroupLifecycle.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/RecordLifecycleActionHeartbeat>`_ **Request Syntax** :: response = client.record_lifecycle_action_heartbeat( LifecycleHookName='string', AutoScalingGroupName='string', LifecycleActionToken='string', InstanceId='string' ) **Response Syntax** :: {} **Response Structure** - *(dict) --* :type LifecycleHookName: string :param LifecycleHookName: **[REQUIRED]** The name of the lifecycle hook. :type AutoScalingGroupName: string :param AutoScalingGroupName: **[REQUIRED]** The name of the Auto Scaling group. :type LifecycleActionToken: string :param LifecycleActionToken: A token that uniquely identifies a specific lifecycle action associated with an instance. Amazon EC2 Auto Scaling sends this token to the notification target that you specified when you created the lifecycle hook. :type InstanceId: string :param InstanceId: The ID of the instance. :rtype: dict :returns: """ pass def resume_processes(self, AutoScalingGroupName: str, ScalingProcesses: List = None): """ Resumes the specified suspended automatic scaling processes, or all suspended process, for the specified Auto Scaling group. For more information, see `Suspending and Resuming Scaling Processes <https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-suspend-resume-processes.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/ResumeProcesses>`_ **Request Syntax** :: response = client.resume_processes( AutoScalingGroupName='string', ScalingProcesses=[ 'string', ] ) :type AutoScalingGroupName: string :param AutoScalingGroupName: **[REQUIRED]** The name of the Auto Scaling group. :type ScalingProcesses: list :param ScalingProcesses: One or more of the following processes. If you omit this parameter, all processes are specified. * ``Launch`` * ``Terminate`` * ``HealthCheck`` * ``ReplaceUnhealthy`` * ``AZRebalance`` * ``AlarmNotification`` * ``ScheduledActions`` * ``AddToLoadBalancer`` - *(string) --* :returns: None """ pass def set_desired_capacity(self, AutoScalingGroupName: str, DesiredCapacity: int, HonorCooldown: bool = None): """ Sets the size of the specified Auto Scaling group. For more information about desired capacity, see `What Is Amazon EC2 Auto Scaling? <https://docs.aws.amazon.com/autoscaling/ec2/userguide/what-is-amazon-ec2-auto-scaling.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/SetDesiredCapacity>`_ **Request Syntax** :: response = client.set_desired_capacity( AutoScalingGroupName='string', DesiredCapacity=123, HonorCooldown=True|False ) :type AutoScalingGroupName: string :param AutoScalingGroupName: **[REQUIRED]** The name of the Auto Scaling group. :type DesiredCapacity: integer :param DesiredCapacity: **[REQUIRED]** The number of EC2 instances that should be running in the Auto Scaling group. :type HonorCooldown: boolean :param HonorCooldown: Indicates whether Amazon EC2 Auto Scaling waits for the cooldown period to complete before initiating a scaling activity to set your Auto Scaling group to its new capacity. By default, Amazon EC2 Auto Scaling does not honor the cooldown period during manual scaling activities. :returns: None """ pass def set_instance_health(self, InstanceId: str, HealthStatus: str, ShouldRespectGracePeriod: bool = None): """ Sets the health status of the specified instance. For more information, see `Health Checks for Auto Scaling Instances <https://docs.aws.amazon.com/autoscaling/ec2/userguide/healthcheck.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/SetInstanceHealth>`_ **Request Syntax** :: response = client.set_instance_health( InstanceId='string', HealthStatus='string', ShouldRespectGracePeriod=True|False ) :type InstanceId: string :param InstanceId: **[REQUIRED]** The ID of the instance. :type HealthStatus: string :param HealthStatus: **[REQUIRED]** The health status of the instance. Set to ``Healthy`` to have the instance remain in service. Set to ``Unhealthy`` to have the instance be out of service. Amazon EC2 Auto Scaling terminates and replaces the unhealthy instance. :type ShouldRespectGracePeriod: boolean :param ShouldRespectGracePeriod: If the Auto Scaling group of the specified instance has a ``HealthCheckGracePeriod`` specified for the group, by default, this call respects the grace period. Set this to ``False`` , to have the call not respect the grace period associated with the group. For more information about the health check grace period, see CreateAutoScalingGroup . :returns: None """ pass def set_instance_protection(self, InstanceIds: List, AutoScalingGroupName: str, ProtectedFromScaleIn: bool) -> Dict: """ Updates the instance protection settings of the specified instances. For more information about preventing instances that are part of an Auto Scaling group from terminating on scale in, see `Instance Protection <https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-instance-termination.html#instance-protection>`__ in the *Amazon EC2 Auto Scaling User Guide* . See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/SetInstanceProtection>`_ **Request Syntax** :: response = client.set_instance_protection( InstanceIds=[ 'string', ], AutoScalingGroupName='string', ProtectedFromScaleIn=True|False ) **Response Syntax** :: {} **Response Structure** - *(dict) --* :type InstanceIds: list :param InstanceIds: **[REQUIRED]** One or more instance IDs. - *(string) --* :type AutoScalingGroupName: string :param AutoScalingGroupName: **[REQUIRED]** The name of the Auto Scaling group. :type ProtectedFromScaleIn: boolean :param ProtectedFromScaleIn: **[REQUIRED]** Indicates whether the instance is protected from termination by Amazon EC2 Auto Scaling when scaling in. :rtype: dict :returns: """ pass def suspend_processes(self, AutoScalingGroupName: str, ScalingProcesses: List = None): """ Suspends the specified automatic scaling processes, or all processes, for the specified Auto Scaling group. If you suspend either the ``Launch`` or ``Terminate`` process types, it can prevent other process types from functioning properly. To resume processes that have been suspended, use ResumeProcesses . For more information, see `Suspending and Resuming Scaling Processes <https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-suspend-resume-processes.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/SuspendProcesses>`_ **Request Syntax** :: response = client.suspend_processes( AutoScalingGroupName='string', ScalingProcesses=[ 'string', ] ) :type AutoScalingGroupName: string :param AutoScalingGroupName: **[REQUIRED]** The name of the Auto Scaling group. :type ScalingProcesses: list :param ScalingProcesses: One or more of the following processes. If you omit this parameter, all processes are specified. * ``Launch`` * ``Terminate`` * ``HealthCheck`` * ``ReplaceUnhealthy`` * ``AZRebalance`` * ``AlarmNotification`` * ``ScheduledActions`` * ``AddToLoadBalancer`` - *(string) --* :returns: None """ pass def terminate_instance_in_auto_scaling_group(self, InstanceId: str, ShouldDecrementDesiredCapacity: bool) -> Dict: """ Terminates the specified instance and optionally adjusts the desired group size. This call simply makes a termination request. The instance is not terminated immediately. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/TerminateInstanceInAutoScalingGroup>`_ **Request Syntax** :: response = client.terminate_instance_in_auto_scaling_group( InstanceId='string', ShouldDecrementDesiredCapacity=True|False ) **Response Syntax** :: { 'Activity': { 'ActivityId': 'string', 'AutoScalingGroupName': 'string', 'Description': 'string', 'Cause': 'string', 'StartTime': datetime(2015, 1, 1), 'EndTime': datetime(2015, 1, 1), 'StatusCode': 'PendingSpotBidPlacement'|'WaitingForSpotInstanceRequestId'|'WaitingForSpotInstanceId'|'WaitingForInstanceId'|'PreInService'|'InProgress'|'WaitingForELBConnectionDraining'|'MidLifecycleAction'|'WaitingForInstanceWarmup'|'Successful'|'Failed'|'Cancelled', 'StatusMessage': 'string', 'Progress': 123, 'Details': 'string' } } **Response Structure** - *(dict) --* - **Activity** *(dict) --* A scaling activity. - **ActivityId** *(string) --* The ID of the activity. - **AutoScalingGroupName** *(string) --* The name of the Auto Scaling group. - **Description** *(string) --* A friendly, more verbose description of the activity. - **Cause** *(string) --* The reason the activity began. - **StartTime** *(datetime) --* The start time of the activity. - **EndTime** *(datetime) --* The end time of the activity. - **StatusCode** *(string) --* The current status of the activity. - **StatusMessage** *(string) --* A friendly, more verbose description of the activity status. - **Progress** *(integer) --* A value between 0 and 100 that indicates the progress of the activity. - **Details** *(string) --* The details about the activity. :type InstanceId: string :param InstanceId: **[REQUIRED]** The ID of the instance. :type ShouldDecrementDesiredCapacity: boolean :param ShouldDecrementDesiredCapacity: **[REQUIRED]** Indicates whether terminating the instance also decrements the size of the Auto Scaling group. :rtype: dict :returns: """ pass def update_auto_scaling_group(self, AutoScalingGroupName: str, LaunchConfigurationName: str = None, LaunchTemplate: Dict = None, MixedInstancesPolicy: Dict = None, MinSize: int = None, MaxSize: int = None, DesiredCapacity: int = None, DefaultCooldown: int = None, AvailabilityZones: List = None, HealthCheckType: str = None, HealthCheckGracePeriod: int = None, PlacementGroup: str = None, VPCZoneIdentifier: str = None, TerminationPolicies: List = None, NewInstancesProtectedFromScaleIn: bool = None, ServiceLinkedRoleARN: str = None): """ Updates the configuration for the specified Auto Scaling group. The new settings take effect on any scaling activities after this call returns. Scaling activities that are currently in progress aren't affected. To update an Auto Scaling group with a launch configuration with ``InstanceMonitoring`` set to ``false`` , you must first disable the collection of group metrics. Otherwise, you get an error. If you have previously enabled the collection of group metrics, you can disable it using DisableMetricsCollection . Note the following: * If you specify a new value for ``MinSize`` without specifying a value for ``DesiredCapacity`` , and the new ``MinSize`` is larger than the current size of the group, we implicitly call SetDesiredCapacity to set the size of the group to the new value of ``MinSize`` . * If you specify a new value for ``MaxSize`` without specifying a value for ``DesiredCapacity`` , and the new ``MaxSize`` is smaller than the current size of the group, we implicitly call SetDesiredCapacity to set the size of the group to the new value of ``MaxSize`` . * All other optional parameters are left unchanged if not specified. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/autoscaling-2011-01-01/UpdateAutoScalingGroup>`_ **Request Syntax** :: response = client.update_auto_scaling_group( AutoScalingGroupName='string', LaunchConfigurationName='string', LaunchTemplate={ 'LaunchTemplateId': 'string', 'LaunchTemplateName': 'string', 'Version': 'string' }, MixedInstancesPolicy={ 'LaunchTemplate': { 'LaunchTemplateSpecification': { 'LaunchTemplateId': 'string', 'LaunchTemplateName': 'string', 'Version': 'string' }, 'Overrides': [ { 'InstanceType': 'string' }, ] }, 'InstancesDistribution': { 'OnDemandAllocationStrategy': 'string', 'OnDemandBaseCapacity': 123, 'OnDemandPercentageAboveBaseCapacity': 123, 'SpotAllocationStrategy': 'string', 'SpotInstancePools': 123, 'SpotMaxPrice': 'string' } }, MinSize=123, MaxSize=123, DesiredCapacity=123, DefaultCooldown=123, AvailabilityZones=[ 'string', ], HealthCheckType='string', HealthCheckGracePeriod=123, PlacementGroup='string', VPCZoneIdentifier='string', TerminationPolicies=[ 'string', ], NewInstancesProtectedFromScaleIn=True|False, ServiceLinkedRoleARN='string' ) :type AutoScalingGroupName: string :param AutoScalingGroupName: **[REQUIRED]** The name of the Auto Scaling group. :type LaunchConfigurationName: string :param LaunchConfigurationName: The name of the launch configuration. If you specify this parameter, you can\'t specify a launch template or a mixed instances policy. :type LaunchTemplate: dict :param LaunchTemplate: The launch template and version to use to specify the updates. If you specify this parameter, you can\'t specify a launch configuration or a mixed instances policy. - **LaunchTemplateId** *(string) --* The ID of the launch template. You must specify either a template ID or a template name. - **LaunchTemplateName** *(string) --* The name of the launch template. You must specify either a template name or a template ID. - **Version** *(string) --* The version number, ``$Latest`` , or ``$Default`` . If the value is ``$Latest`` , Amazon EC2 Auto Scaling selects the latest version of the launch template when launching instances. If the value is ``$Default`` , Amazon EC2 Auto Scaling selects the default version of the launch template when launching instances. The default value is ``$Default`` . :type MixedInstancesPolicy: dict :param MixedInstancesPolicy: The mixed instances policy to use to specify the updates. If you specify this parameter, you can\'t specify a launch configuration or a launch template. For more information, see `Auto Scaling Groups with Multiple Instance Types and Purchase Options <https://docs.aws.amazon.com/autoscaling/ec2/userguide/asg-purchase-options.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . - **LaunchTemplate** *(dict) --* The launch template and overrides. This parameter is required when creating an Auto Scaling group with a mixed instances policy, but is not required when updating the group. - **LaunchTemplateSpecification** *(dict) --* The launch template to use. You must specify either the launch template ID or launch template name in the request. - **LaunchTemplateId** *(string) --* The ID of the launch template. You must specify either a template ID or a template name. - **LaunchTemplateName** *(string) --* The name of the launch template. You must specify either a template name or a template ID. - **Version** *(string) --* The version number, ``$Latest`` , or ``$Default`` . If the value is ``$Latest`` , Amazon EC2 Auto Scaling selects the latest version of the launch template when launching instances. If the value is ``$Default`` , Amazon EC2 Auto Scaling selects the default version of the launch template when launching instances. The default value is ``$Default`` . - **Overrides** *(list) --* Any parameters that you specify override the same parameters in the launch template. Currently, the only supported override is instance type. You must specify between 2 and 20 overrides. - *(dict) --* Describes an override for a launch template. - **InstanceType** *(string) --* The instance type. For information about available instance types, see `Available Instance Types <https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/instance-types.html#AvailableInstanceTypes>`__ in the *Amazon Elastic Compute Cloud User Guide.* - **InstancesDistribution** *(dict) --* The instances distribution to use. If you leave this parameter unspecified when creating the group, the default values are used. - **OnDemandAllocationStrategy** *(string) --* Indicates how to allocate instance types to fulfill On-Demand capacity. The only valid value is ``prioritized`` , which is also the default value. This strategy uses the order of instance type overrides for the LaunchTemplate to define the launch priority of each instance type. The first instance type in the array is prioritized higher than the last. If all your On-Demand capacity cannot be fulfilled using your highest priority instance, then the Auto Scaling groups launches the remaining capacity using the second priority instance type, and so on. - **OnDemandBaseCapacity** *(integer) --* The minimum amount of the Auto Scaling group\'s capacity that must be fulfilled by On-Demand Instances. This base portion is provisioned first as your group scales. The default value is ``0`` . If you leave this parameter set to ``0`` , On-Demand Instances are launched as a percentage of the Auto Scaling group\'s desired capacity, per the ``OnDemandPercentageAboveBaseCapacity`` setting. - **OnDemandPercentageAboveBaseCapacity** *(integer) --* Controls the percentages of On-Demand Instances and Spot Instances for your additional capacity beyond ``OnDemandBaseCapacity`` . The range is 0–100. The default value is ``100`` . If you leave this parameter set to ``100`` , the percentages are 100% for On-Demand Instances and 0% for Spot Instances. - **SpotAllocationStrategy** *(string) --* Indicates how to allocate Spot capacity across Spot pools. The only valid value is ``lowest-price`` , which is also the default value. The Auto Scaling group selects the cheapest Spot pools and evenly allocates your Spot capacity across the number of Spot pools that you specify. - **SpotInstancePools** *(integer) --* The number of Spot pools to use to allocate your Spot capacity. The Spot pools are determined from the different instance types in the Overrides array of LaunchTemplate . The range is 1–20 and the default is 2. - **SpotMaxPrice** *(string) --* The maximum price per unit hour that you are willing to pay for a Spot Instance. If you leave the value of this parameter blank (which is the default), the maximum Spot price is set at the On-Demand price. To remove a value that you previously set, include the parameter but leave the value blank. :type MinSize: integer :param MinSize: The minimum size of the Auto Scaling group. :type MaxSize: integer :param MaxSize: The maximum size of the Auto Scaling group. :type DesiredCapacity: integer :param DesiredCapacity: The number of EC2 instances that should be running in the Auto Scaling group. This number must be greater than or equal to the minimum size of the group and less than or equal to the maximum size of the group. :type DefaultCooldown: integer :param DefaultCooldown: The amount of time, in seconds, after a scaling activity completes before another scaling activity can start. The default value is ``300`` . For more information, see `Scaling Cooldowns <https://docs.aws.amazon.com/autoscaling/ec2/userguide/Cooldown.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . :type AvailabilityZones: list :param AvailabilityZones: One or more Availability Zones for the group. - *(string) --* :type HealthCheckType: string :param HealthCheckType: The service to use for the health checks. The valid values are ``EC2`` and ``ELB`` . If you configure an Auto Scaling group to use ELB health checks, it considers the instance unhealthy if it fails either the EC2 status checks or the load balancer health checks. :type HealthCheckGracePeriod: integer :param HealthCheckGracePeriod: The amount of time, in seconds, that Amazon EC2 Auto Scaling waits before checking the health status of an EC2 instance that has come into service. The default value is ``0`` . For more information, see `Health Checks for Auto Scaling Instances <https://docs.aws.amazon.com/autoscaling/ec2/userguide/healthcheck.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . Conditional: This parameter is required if you are adding an ``ELB`` health check. :type PlacementGroup: string :param PlacementGroup: The name of the placement group into which to launch your instances, if any. A placement group is a logical grouping of instances within a single Availability Zone. You cannot specify multiple Availability Zones and a placement group. For more information, see `Placement Groups <https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/placement-groups.html>`__ in the *Amazon EC2 User Guide for Linux Instances* . :type VPCZoneIdentifier: string :param VPCZoneIdentifier: A comma-separated list of subnet IDs, if you are launching into a VPC. If you specify ``VPCZoneIdentifier`` with ``AvailabilityZones`` , the subnets that you specify for this parameter must reside in those Availability Zones. :type TerminationPolicies: list :param TerminationPolicies: A standalone termination policy or a list of termination policies used to select the instance to terminate. The policies are executed in the order that they are listed. For more information, see `Controlling Which Instances Auto Scaling Terminates During Scale In <https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-instance-termination.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . - *(string) --* :type NewInstancesProtectedFromScaleIn: boolean :param NewInstancesProtectedFromScaleIn: Indicates whether newly launched instances are protected from termination by Amazon EC2 Auto Scaling when scaling in. For more information about preventing instances from terminating on scale in, see `Instance Protection <https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-instance-termination.html#instance-protection>`__ in the *Amazon EC2 Auto Scaling User Guide* . :type ServiceLinkedRoleARN: string :param ServiceLinkedRoleARN: The Amazon Resource Name (ARN) of the service-linked role that the Auto Scaling group uses to call other AWS services on your behalf. For more information, see `Service-Linked Roles <https://docs.aws.amazon.com/autoscaling/ec2/userguide/autoscaling-service-linked-role.html>`__ in the *Amazon EC2 Auto Scaling User Guide* . :returns: None """ pass

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55900099413e9b0b80c767c287044188363f1e04

144

py

Python

tests/unit/conftest.py

radeklat/issue-watcher

5f60025d11f9b262908ac3efb41b42df61f65b3e

[ "MIT" ]

4

2019-08-08T10:59:37.000Z

2020-02-26T17:00:59.000Z

tests/unit/conftest.py

radeklat/issue-watcher

5f60025d11f9b262908ac3efb41b42df61f65b3e

[ "MIT" ]

13

2019-08-03T18:38:29.000Z

2022-01-21T23:47:31.000Z

tests/unit/conftest.py

radeklat/issue-watcher

5f60025d11f9b262908ac3efb41b42df61f65b3e

[ "MIT" ]

null

from tests.unit.github.fixtures import assert_github_issue_no_cache, requests_mock __all__ = ["assert_github_issue_no_cache", "requests_mock"]

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py

Python

tests/caches/snapshots/snap_test_db.py

ColeVoelpel/virtool

859c8d2516f07343bde47f3bae0247dedd76e6c4

[ "MIT" ]

1

2019-08-23T00:19:00.000Z

tests/caches/snapshots/snap_test_db.py

ColeVoelpel/virtool

859c8d2516f07343bde47f3bae0247dedd76e6c4

[ "MIT" ]

null

tests/caches/snapshots/snap_test_db.py

ColeVoelpel/virtool

859c8d2516f07343bde47f3bae0247dedd76e6c4

[ "MIT" ]

null

# -*- coding: utf-8 -*- # snapshottest: v1 - https://goo.gl/zC4yUc from __future__ import unicode_literals from snapshottest import GenericRepr, Snapshot snapshots = Snapshot() snapshots['test_create_duplicate return'] = { 'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'), 'files': [ ], 'hash': '68b60be51a667882d3aaa02a93259dd526e9c990', 'id': 'u3cuwaoq', 'legacy': False, 'missing': False, 'paired': False, 'parameters': { 'end_quality': '20', 'max_error_rate': '0.1', 'max_indel_rate': '0.03', 'max_length': None, 'mean_quality': '25', 'min_length': '20', 'mode': 'pe' }, 'program': 'skewer-0.2.2', 'ready': False, 'sample': { 'id': 'foo' } } snapshots['test_create_duplicate db'] = { '_id': 'u3cuwaoq', 'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'), 'files': [ ], 'hash': '68b60be51a667882d3aaa02a93259dd526e9c990', 'legacy': False, 'missing': False, 'paired': False, 'parameters': { 'end_quality': '20', 'max_error_rate': '0.1', 'max_indel_rate': '0.03', 'max_length': None, 'mean_quality': '25', 'min_length': '20', 'mode': 'pe' }, 'program': 'skewer-0.2.2', 'ready': False, 'sample': { 'id': 'foo' } } snapshots['test_create[paired] return'] = { 'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'), 'files': [ ], 'hash': '68b60be51a667882d3aaa02a93259dd526e9c990', 'id': '9pfsom1b', 'legacy': False, 'missing': False, 'paired': True, 'parameters': { 'end_quality': '20', 'max_error_rate': '0.1', 'max_indel_rate': '0.03', 'max_length': None, 'mean_quality': '25', 'min_length': '20', 'mode': 'pe' }, 'program': 'skewer-0.2.2', 'ready': False, 'sample': { 'id': 'foo' } } snapshots['test_create[paired] db'] = { '_id': '9pfsom1b', 'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'), 'files': [ ], 'hash': '68b60be51a667882d3aaa02a93259dd526e9c990', 'legacy': False, 'missing': False, 'paired': True, 'parameters': { 'end_quality': '20', 'max_error_rate': '0.1', 'max_indel_rate': '0.03', 'max_length': None, 'mean_quality': '25', 'min_length': '20', 'mode': 'pe' }, 'program': 'skewer-0.2.2', 'ready': False, 'sample': { 'id': 'foo' } } snapshots['test_create[unpaired] return'] = { 'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'), 'files': [ ], 'hash': '68b60be51a667882d3aaa02a93259dd526e9c990', 'id': '9pfsom1b', 'legacy': False, 'missing': False, 'paired': False, 'parameters': { 'end_quality': '20', 'max_error_rate': '0.1', 'max_indel_rate': '0.03', 'max_length': None, 'mean_quality': '25', 'min_length': '20', 'mode': 'pe' }, 'program': 'skewer-0.2.2', 'ready': False, 'sample': { 'id': 'foo' } } snapshots['test_create[unpaired] db'] = { '_id': '9pfsom1b', 'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'), 'files': [ ], 'hash': '68b60be51a667882d3aaa02a93259dd526e9c990', 'legacy': False, 'missing': False, 'paired': False, 'parameters': { 'end_quality': '20', 'max_error_rate': '0.1', 'max_indel_rate': '0.03', 'max_length': None, 'mean_quality': '25', 'min_length': '20', 'mode': 'pe' }, 'program': 'skewer-0.2.2', 'ready': False, 'sample': { 'id': 'foo' } } snapshots['test_create_legacy return'] = { 'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'), 'files': [ ], 'hash': '68b60be51a667882d3aaa02a93259dd526e9c990', 'id': '9pfsom1b', 'legacy': True, 'missing': False, 'paired': False, 'parameters': { 'end_quality': '20', 'max_error_rate': '0.1', 'max_indel_rate': '0.03', 'max_length': None, 'mean_quality': '25', 'min_length': '20', 'mode': 'pe' }, 'program': 'skewer-0.2.2', 'ready': False, 'sample': { 'id': 'foo' } } snapshots['test_create_legacy db'] = { '_id': '9pfsom1b', 'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'), 'files': [ ], 'hash': '68b60be51a667882d3aaa02a93259dd526e9c990', 'legacy': True, 'missing': False, 'paired': False, 'parameters': { 'end_quality': '20', 'max_error_rate': '0.1', 'max_indel_rate': '0.03', 'max_length': None, 'mean_quality': '25', 'min_length': '20', 'mode': 'pe' }, 'program': 'skewer-0.2.2', 'ready': False, 'sample': { 'id': 'foo' } } snapshots['test_create_program return'] = { 'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'), 'files': [ ], 'hash': '68b60be51a667882d3aaa02a93259dd526e9c990', 'id': '9pfsom1b', 'legacy': False, 'missing': False, 'paired': False, 'parameters': { 'end_quality': '20', 'max_error_rate': '0.1', 'max_indel_rate': '0.03', 'max_length': None, 'mean_quality': '25', 'min_length': '20', 'mode': 'pe' }, 'program': 'trimmomatic-0.2.3', 'ready': False, 'sample': { 'id': 'foo' } } snapshots['test_create_program db'] = { '_id': '9pfsom1b', 'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'), 'files': [ ], 'hash': '68b60be51a667882d3aaa02a93259dd526e9c990', 'legacy': False, 'missing': False, 'paired': False, 'parameters': { 'end_quality': '20', 'max_error_rate': '0.1', 'max_indel_rate': '0.03', 'max_length': None, 'mean_quality': '25', 'min_length': '20', 'mode': 'pe' }, 'program': 'trimmomatic-0.2.3', 'ready': False, 'sample': { 'id': 'foo' } }

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4.971474

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0.278179

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0

7

55bf337e7a53ea3faeab125f6b973cc3203762d5

3,926

py

Python

Loop_Induced_Vertices/lorentz_ggSS.py

ycwu1030/2HDM_FR

599490fd785cb67e3e4ffad1fa7536906ac8bcd5

[ "MIT" ]

1

2019-09-04T01:44:29.000Z

Loop_Induced_Vertices/lorentz_ggSS.py

ycwu1030/2HDM_FR

599490fd785cb67e3e4ffad1fa7536906ac8bcd5

[ "MIT" ]

null

Loop_Induced_Vertices/lorentz_ggSS.py

ycwu1030/2HDM_FR

599490fd785cb67e3e4ffad1fa7536906ac8bcd5

[ "MIT" ]

null

VVSSFtop = Lorentz(name = 'VVSSFtop', spins = [ 3, 3, 1, 1 ], structure = 'FBoxEvenTop(P(-1,1)*P(-1,2),P(-1,1)*P(-1,3),P(-1,2)*P(-1,3),P(-1,3)*P(-1,3)) * (Metric(1,2)*P(-1,1)*P(-1,2) - P(2,1)*P(1,2))') VVSSFbot = Lorentz(name = 'VVSSFbot', spins = [ 3, 3, 1, 1 ], structure = 'FBoxEvenBot(P(-1,1)*P(-1,2),P(-1,1)*P(-1,3),P(-1,2)*P(-1,3),P(-1,3)*P(-1,3)) * (Metric(1,2)*P(-1,1)*P(-1,2) - P(2,1)*P(1,2))') VVSSGtop = Lorentz(name = 'VVSSGtop', spins = [ 3, 3, 1, 1 ], structure = 'GBoxEvenTop(P(-1,1)*P(-1,2),P(-1,1)*P(-1,3),P(-1,2)*P(-1,3),P(-1,3)*P(-1,3)) * (2*Metric(1,2)*(P(-1,1)*P(-1,3))*(P(-2,2)*P(-2,3)) - (P(-1,3)*P(-1,3))*(P(-2,1)*P(-2,2))*Metric(1,2) + (P(-1,3)*P(-1,3))*P(1,2)*P(2,1) - 2*(P(-1,2)*P(-1,3))*P(2,1)*P(1,3) - 2*(P(-1,1)*P(-1,3))*P(1,2)*P(2,3) + 2*(P(-1,1)*P(-1,2))*P(1,3)*P(2,3))') VVSSGbot = Lorentz(name = 'VVSSGbot', spins = [ 3, 3, 1, 1 ], structure = 'GBoxEvenBot(P(-1,1)*P(-1,2),P(-1,1)*P(-1,3),P(-1,2)*P(-1,3),P(-1,3)*P(-1,3)) * (2*Metric(1,2)*(P(-1,1)*P(-1,3))*(P(-2,2)*P(-2,3)) - (P(-1,3)*P(-1,3))*(P(-2,1)*P(-2,2))*Metric(1,2) + (P(-1,3)*P(-1,3))*P(1,2)*P(2,1) - 2*(P(-1,2)*P(-1,3))*P(2,1)*P(1,3) - 2*(P(-1,1)*P(-1,3))*P(1,2)*P(2,3) + 2*(P(-1,1)*P(-1,2))*P(1,3)*P(2,3))') VVAAFtop = Lorentz(name = 'VVAAFtop', spins = [ 3, 3, 1, 1 ], structure = 'FBoxOddTop(P(-1,1)*P(-1,2),P(-1,1)*P(-1,3),P(-1,2)*P(-1,3),P(-1,3)*P(-1,3)) * (Metric(1,2)*P(-1,1)*P(-1,2) - P(2,1)*P(1,2))') VVAAFbot = Lorentz(name = 'VVAAFbot', spins = [ 3, 3, 1, 1 ], structure = 'FBoxOddBot(P(-1,1)*P(-1,2),P(-1,1)*P(-1,3),P(-1,2)*P(-1,3),P(-1,3)*P(-1,3)) * (Metric(1,2)*P(-1,1)*P(-1,2) - P(2,1)*P(1,2))') VVAAGtop = Lorentz(name = 'VVAAGtop', spins = [ 3, 3, 1, 1 ], structure = 'GBoxOddTop(P(-1,1)*P(-1,2),P(-1,1)*P(-1,3),P(-1,2)*P(-1,3),P(-1,3)*P(-1,3)) * (2*Metric(1,2)*(P(-1,1)*P(-1,3))*(P(-2,2)*P(-2,3)) - (P(-1,3)*P(-1,3))*(P(-2,1)*P(-2,2))*Metric(1,2) + (P(-1,3)*P(-1,3))*P(1,2)*P(2,1) - 2*(P(-1,2)*P(-1,3))*P(2,1)*P(1,3) - 2*(P(-1,1)*P(-1,3))*P(1,2)*P(2,3) + 2*(P(-1,1)*P(-1,2))*P(1,3)*P(2,3))') VVAAGbot = Lorentz(name = 'VVAAGbot', spins = [ 3, 3, 1, 1 ], structure = 'GBoxOddBot(P(-1,1)*P(-1,2),P(-1,1)*P(-1,3),P(-1,2)*P(-1,3),P(-1,3)*P(-1,3)) * (2*Metric(1,2)*(P(-1,1)*P(-1,3))*(P(-2,2)*P(-2,3)) - (P(-1,3)*P(-1,3))*(P(-2,1)*P(-2,2))*Metric(1,2) + (P(-1,3)*P(-1,3))*P(1,2)*P(2,1) - 2*(P(-1,2)*P(-1,3))*P(2,1)*P(1,3) - 2*(P(-1,1)*P(-1,3))*P(1,2)*P(2,3) + 2*(P(-1,1)*P(-1,2))*P(1,3)*P(2,3))') VVSAFtop = Lorentz(name = 'VVSAFtop', spins = [ 3, 3, 1, 1 ], structure = 'FBoxSATop(P(-1,1)*P(-1,2),P(-1,1)*P(-1,3),P(-1,2)*P(-1,3),P(-1,3)*P(-1,3)) * (Epsilon(1,2,-1,-2)*P(-1,1)*P(-2,2))') VVSAFbot = Lorentz(name = 'VVSAFbot', spins = [ 3, 3, 1, 1 ], structure = 'FBoxSABot(P(-1,1)*P(-1,2),P(-1,1)*P(-1,3),P(-1,2)*P(-1,3),P(-1,3)*P(-1,3)) * (Epsilon(1,2,-1,-2)*P(-1,1)*P(-2,2))') VVSAGtop = Lorentz(name = 'VVSAGtop', spins = [ 3, 3, 1, 1 ], structure = 'GBoxSATop(P(-1,1)*P(-1,2),P(-1,1)*P(-1,3),P(-1,2)*P(-1,3),P(-1,3)*P(-1,3)) * (Epsilon(2,-1,-2,-3)*P(-1,1)*P(-2,2)*P(-3,3)*P(1,3)+Epsilon(1,-1,-2,-3)*P(-1,1)*P(-2,2)*P(-3,3)*P(2,3)+Epsilon(1,2,-1,-3)*P(-1,1)*P(-3,3)*P(-2,2)*P(-2,3)+Epsilon(1,2,-2,-3)*P(-2,2)*P(-3,3)*P(-1,1)*P(-1,3))') VVSAGbot = Lorentz(name = 'VVSAGbot', spins = [ 3, 3, 1, 1 ], structure = 'GBoxSABot(P(-1,1)*P(-1,2),P(-1,1)*P(-1,3),P(-1,2)*P(-1,3),P(-1,3)*P(-1,3)) * (Epsilon(2,-1,-2,-3)*P(-1,1)*P(-2,2)*P(-3,3)*P(1,3)+Epsilon(1,-1,-2,-3)*P(-1,1)*P(-2,2)*P(-3,3)*P(2,3)+Epsilon(1,2,-1,-3)*P(-1,1)*P(-3,3)*P(-2,2)*P(-2,3)+Epsilon(1,2,-2,-3)*P(-2,2)*P(-3,3)*P(-1,1)*P(-1,3))')

80.122449

354

0.411105

966

3,926

1.670807

0.035197

0.230483

0.163569

0.168525

0.724907

0.591078

0

0.190006

0.174223

3,926

48

355

81.791667

0.307835

0

0.333333

0

0.333333

0.679236

0.612994

0

1

0

false

0

1

null

1

0

1

0

1

0

1

0

1

null

0

8

e94d406f31245af57723830a02b7452c13bef1f2

23,864

py

Python

poco/tests/poco_test.py

gaborkolarovics/poco

31237ce9138c134e7780cd3ed7459cd5f4e07834

[ "MIT" ]

52

2017-10-13T06:11:41.000Z

2021-12-08T08:08:48.000Z

poco/tests/poco_test.py

gaborkolarovics/poco

31237ce9138c134e7780cd3ed7459cd5f4e07834

[ "MIT" ]

28

2017-08-02T13:55:53.000Z

2017-09-07T14:31:55.000Z

poco/tests/poco_test.py

gaborkolarovics/poco

31237ce9138c134e7780cd3ed7459cd5f4e07834

[ "MIT" ]

8

2018-02-16T10:51:27.000Z

2022-02-04T11:17:44.000Z

import git import os import yaml import poco.poco as poco from .abstract_test import AbstractTestSuite from poco.services.file_utils import FileUtils from poco.services.cta_utils import CTAUtils class PocoTestSuite(AbstractTestSuite): def test_without_command(self): with self.captured_output() as (out, err): with self.assertRaises(SystemExit) as context: self.run_poco_command() self.assertIsNotNone(context.exception) self.assertIn(poco.__doc__.strip(), out.getvalue().strip()) self.assertIn(poco.END_STRING.strip(), out.getvalue().strip()) def test_version(self): with self.captured_output() as (out, err): with self.assertRaises(SystemExit) as context: self.run_poco_command("--version") self.assertIsNotNone(context.exception) self.assertIn(poco.__version__, out.getvalue().strip()) def test_help_command(self): with self.captured_output() as (out, err): with self.assertRaises(SystemExit) as context: self.run_poco_command("help") self.assertIsNotNone(context.exception) self.assertIn(poco.__doc__.strip(), out.getvalue().strip()) self.assertIn(CTAUtils.CTA_STRINGS['default'], out.getvalue()) def test_help_command_with_catalog(self): self.init_with_local_catalog() with self.captured_output() as (out, err): with self.assertRaises(SystemExit) as context: self.run_poco_command("help") self.assertIsNotNone(context.exception) self.assertIn(poco.__doc__.strip(), out.getvalue().strip()) self.assertIn(CTAUtils.CTA_STRINGS['have_cat'], out.getvalue()) def test_help_command_with_poco_file(self): self.init_empty_compose_file() with self.captured_output() as (out, err): with self.assertRaises(SystemExit) as context: self.run_poco_command("help") self.assertIsNotNone(context.exception) self.assertIn(poco.__doc__.strip(), out.getvalue().strip()) self.assertIn(CTAUtils.CTA_STRINGS['have_file'], out.getvalue()) def test_help_command_with_everything(self): self.init_empty_compose_file() self.init_poco_file() with self.captured_output() as (out, err): with self.assertRaises(SystemExit) as context: self.run_poco_command("help") self.assertIsNotNone(context.exception) self.assertIn(poco.__doc__.strip(), out.getvalue().strip()) self.assertIn(CTAUtils.CTA_STRINGS['have_all'], out.getvalue()) def test_subcommand_help(self): with self.captured_output() as (out, err): with self.assertRaises(SystemExit) as context: self.run_poco_command("repo") self.assertIsNotNone(context.exception) output = out.getvalue().strip() self.assertIn("Poco repo commands\n", output) self.assertIn("Usage:", output) def test_wrong_parameters(self): with self.captured_output() as (out, err): with self.assertRaises(SystemExit) as context: self.run_poco_command("notexistcommand") self.assertIsNotNone(context.exception) self.assertIn(poco.__doc__.strip(), out.getvalue().strip()) self.assertIn("\'notexistcommand\' is not a poco command.", out.getvalue().strip()) def test_config_without_config(self): with self.captured_output() as (out, err): self.run_poco_command("repo", "ls") self.assertIn("Actual config\n-------------\n", out.getvalue().strip()) def test_config_with_config(self): self.init_with_remote_catalog() with self.captured_output() as (out, err): self.run_poco_command("repo", "ls") out_string = out.getvalue().strip() self.assertIn("Actual config\n-------------\n", out_string) self.assertIn("Mode: developer\nOffline: False\nAlways update: False", out_string) self.assertIn("Working directory: " + str(self.ws_dir), out_string) self.assertIn("Config location: " + str(self.config_file), out_string) self.assertIn(yaml.dump(AbstractTestSuite.REMOTE_CONFIG, default_flow_style=False, default_style='', indent=4) .strip(), out_string) def test_config_with_config_and_demo_mode(self): extra_config = dict() extra_config['mode'] = 'demo' self.init_with_remote_catalog(extra_config) with self.captured_output() as (out, err): self.run_poco_command("repo", "ls") out_string = out.getvalue().strip() self.assertIn("Actual config\n-------------\n", out_string) self.assertIn("Mode: demo\nOffline: False\nAlways update: True", out_string) self.assertIn("Working directory: " + str(self.ws_dir), out_string) self.assertIn("Config location: " + str(self.config_file), out_string) self.assertIn(yaml.dump(AbstractTestSuite.REMOTE_CONFIG, default_flow_style=False, default_style='', indent=4) .strip(), out_string) def test_config_with_config_and_server_mode(self): extra_config = dict() extra_config['mode'] = 'server' self.init_with_remote_catalog(extra_config) os.mkdir(os.path.join(self.tmpdir, 'catalogHome')) os.mkdir(os.path.join(self.tmpdir, 'catalogHome', 'default')) with self.captured_output() as (out, err): self.run_poco_command("repo", "ls") out_string = out.getvalue().strip() self.assertIn("Actual config\n-------------\n", out_string) self.assertIn("Mode: server\nOffline: True\nAlways update: False", out_string) self.assertIn("Working directory: " + str(self.ws_dir), out_string) self.assertIn("Config location: " + str(self.config_file), out_string) self.assertIn(yaml.dump(AbstractTestSuite.REMOTE_CONFIG, default_flow_style=False, default_style='', indent=4) .strip(), out_string) def test_config_with_config_and_options(self): self.init_with_local_catalog() with self.captured_output() as (out, err): self.run_poco_command("--offline", "--always-update", "repo", "ls") out_string = out.getvalue().strip() self.assertIn("Actual config\n-------------\n", out_string) self.assertIn("Mode: developer\nOffline: True\nAlways update: True", out_string) self.assertIn("Working directory: " + str(self.ws_dir), out_string) self.assertIn("Config location: " + str(self.config_file), out_string) self.assertIn(yaml.dump(AbstractTestSuite.LOCAL_CONFIG, default_flow_style=False, default_style='', indent=4) .strip(), out_string) def test_catalog_without_catalog(self): with self.captured_output() as (out, err): with self.assertRaises(SystemExit) as context: self.run_poco_command("catalog") self.assertIsNotNone(context.exception) self.assertEqual(0, len(err.getvalue())) self.assertIn(CTAUtils.CTA_STRINGS['default'], out.getvalue().strip()) self.assertIn("You have not catalog yet.", out.getvalue().strip()) def test_catalog_with_empty_catalog(self): with open(self.config_file, 'w+') as stream: data = dict() data['default'] = dict() yaml.dump(data=data, stream=stream, default_flow_style=False, default_style='', indent=4) with self.captured_output() as (out, err): self.run_poco_command("catalog") self.assertEqual(0, len(err.getvalue())) self.assertIn("Project catalog is empty. You can add projects with 'poco repo add' command", out.getvalue().strip()) def test_catalog(self): self.init_with_remote_catalog() with self.captured_output() as (out, err): self.run_poco_command("catalog") self.assertEqual(0, len(err.getvalue())) catalog = out.getvalue().strip() self.assertIn("Available projects:", catalog) with self.captured_output() as (out, err): self.run_poco_command("project", "ls") self.assertEqual(0, len(err.getvalue())) self.assertEqual(catalog, out.getvalue().strip()) def test_catalog_with_param_that_not_exists(self): self.init_with_remote_catalog() with self.captured_output() as (out, err): with self.assertRaises(SystemExit) as context: self.run_poco_command("catalog", "asd") self.assertIsNotNone(context.exception) self.assertEqual(0, len(err.getvalue())) catalog = out.getvalue().strip() self.assertNotIn("Available projects:", catalog) with self.captured_output() as (out, err): with self.assertRaises(SystemExit) as context: self.run_poco_command("project", "ls", "asd") self.assertIsNotNone(context.exception) self.assertEqual(0, len(err.getvalue())) self.assertEqual(catalog, out.getvalue().strip()) def test_catalog_with_param(self): self.init_with_remote_catalog() with self.captured_output() as (out, err): self.run_poco_command("catalog", "default") self.assertEqual(0, len(err.getvalue())) catalog = out.getvalue().strip() self.assertIn("Available projects:", catalog) with self.captured_output() as (out, err): self.run_poco_command("project", "ls") self.assertEqual(0, len(err.getvalue())) self.assertEqual(catalog, out.getvalue().strip()) def test_add_modify_and_remove_config(self): self.init_with_remote_catalog() with self.captured_output() as (out, err): self.run_poco_command("repo", "add", "test", "https://github.com/shiwaforce/poco-example", "master", "poco-catalog.yaml") self.assertEqual(0, len(err.getvalue())) data = dict() data["test"] = dict() data["test"]["branch"] = "master" data["test"]["file"] = "poco-catalog.yaml" data["test"]["repositoryType"] = "git" data["test"]["server"] = "https://github.com/shiwaforce/poco-example" self.assertIn(yaml.dump(data, default_flow_style=False, default_style='', indent=4).strip(), out.getvalue().strip()) self.clean_states() with self.captured_output() as (out, err): self.run_poco_command("repo", "modify", "test", "https://github.com/shiwaforce/procok.git", "master", "test2.yml") data["test"]["branch"] = "master" data["test"]["file"] = "test2.yml" data["test"]["server"] = "https://github.com/shiwaforce/procok.git" self.assertIn(yaml.dump(data, default_flow_style=False, default_style='', indent=4).strip(), out.getvalue().strip()) self.clean_states() with self.captured_output() as (out, err): self.run_poco_command("--offline", "repo", "remove", "test") self.assertEqual(0, len(err.getvalue())) self.assertNotIn("test", out.getvalue().strip()) def test_add_modify_and_remove_config_github(self): self.init_with_remote_catalog() with self.captured_output() as (out, err): self.run_poco_command("github", "add", "test", "thisistoken", "http://test/test") self.assertEqual(0, len(err.getvalue())) data = dict() data["test"] = dict() data["test"]["token"] = "thisistoken" data["test"]["repositoryType"] = "github" data["test"]["server"] = "http://test/test" self.assertIn(yaml.dump(data, default_flow_style=False, default_style='', indent=4).strip(), out.getvalue().strip()) self.clean_states() with self.captured_output() as (out, err): self.run_poco_command("github", "modify", "test", "user/pass") data = dict() data["test"] = dict() data["test"]["user"] = "user" data["test"]["pass"] = "pass" data["test"]["repositoryType"] = "github" self.assertIn(yaml.dump(data, default_flow_style=False, default_style='', indent=4).strip(), out.getvalue().strip()) self.clean_states() with self.captured_output() as (out, err): self.run_poco_command("--offline", "repo", "remove", "test") self.assertEqual(0, len(err.getvalue())) self.assertNotIn("test", out.getvalue().strip()) def test_add_modify_and_remove_config_gitlab(self): self.init_with_remote_catalog() with self.captured_output() as (out, err): self.run_poco_command("gitlab", "add", "test", "xxxxxx", "http://test/test", "/ssh/ssh2") self.assertEqual(0, len(err.getvalue())) data = dict() data["test"] = dict() data["test"]["token"] = "xxxxxx" data["test"]["repositoryType"] = "gitlab" data["test"]["server"] = "http://test/test" data["test"]["ssh"] = "/ssh/ssh2" self.assertIn(yaml.dump(data, default_flow_style=False, default_style='', indent=4).strip(), out.getvalue().strip()) self.clean_states() with self.captured_output() as (out, err): self.run_poco_command("gitlab", "modify", "test", "anothertoken") data = dict() data["test"] = dict() data["test"]["token"] = "anothertoken" data["test"]["repositoryType"] = "gitlab" self.assertIn(yaml.dump(data, default_flow_style=False, default_style='', indent=4).strip(), out.getvalue().strip()) self.clean_states() with self.captured_output() as (out, err): self.run_poco_command("--offline", "repo", "remove", "test") self.assertEqual(0, len(err.getvalue())) self.assertNotIn("test", out.getvalue().strip()) def test_add_modify_and_remove_config_bitbucket(self): self.init_with_remote_catalog() with self.captured_output() as (out, err): self.run_poco_command("bitbucket", "add", "test", "user/pass", "http://test/test", "/ssh/ssh2") self.assertEqual(0, len(err.getvalue())) data = dict() data["test"] = dict() data["test"]["user"] = "user" data["test"]["pass"] = "pass" data["test"]["repositoryType"] = "bitbucket" data["test"]["server"] = "http://test/test" data["test"]["ssh"] = "/ssh/ssh2" self.assertIn(yaml.dump(data, default_flow_style=False, default_style='', indent=4).strip(), out.getvalue().strip()) self.clean_states() with self.captured_output() as (out, err): self.run_poco_command("bitbucket", "modify", "test", "user2/pass2") data = dict() data["test"] = dict() data["test"]["user"] = "user2" data["test"]["pass"] = "pass2" data["test"]["repositoryType"] = "bitbucket" self.assertIn(yaml.dump(data, default_flow_style=False, default_style='', indent=4).strip(), out.getvalue().strip()) self.clean_states() with self.captured_output() as (out, err): self.run_poco_command("--offline", "repo", "remove", "test") self.assertEqual(0, len(err.getvalue())) self.assertNotIn("test", out.getvalue().strip()) def test_add_if_catalog_not_exists(self): with self.captured_output() as (out, err): self.run_poco_command("repo", "add", "test", "https://github.com/shiwaforce/poco-example", "master", "poco-catalog.yaml") self.assertEqual(0, len(err.getvalue())) data = dict() data["test"] = dict() data["test"]["branch"] = "master" data["test"]["file"] = "poco-catalog.yaml" data["test"]["repositoryType"] = "git" data["test"]["server"] = "https://github.com/shiwaforce/poco-example" self.assertIn(yaml.dump(data, default_flow_style=False, default_style='', indent=4).strip(), out.getvalue().strip()) def test_branches_with_local_config(self): self.init_with_local_catalog() with self.captured_output() as (out, err): self.run_poco_command("repo", "branches") self.assertEqual(0, len(err.getvalue().strip())) self.assertIn('Branch is not supported in this repository.', out.getvalue().strip()) def test_branches_with_remote_config(self): self.init_with_remote_catalog() with self.captured_output() as (out, err): self.run_poco_command("repo", "branches") self.assertEqual(0, len(err.getvalue().strip())) self.assertIn('Available branches in', out.getvalue().strip()) self.assertIn('master', out.getvalue().strip()) def test_switch_branch_with_local_config(self): self.init_with_local_catalog() with self.assertRaises(SystemExit) as context: self.run_poco_command("repo", "branch", "master") self.assertEqual(1, context.exception.code) def test_switch_branch_with_remote_config(self): self.init_with_remote_catalog() with self.captured_output() as (out, err): self.run_poco_command("repo", "branch", "master") self.assertIn("Branch changed", out.getvalue()) def test_push_with_local_config(self): self.init_with_local_catalog() with self.captured_output() as (out, err): self.run_poco_command("repo", "push") self.assertEqual(0, len(err.getvalue().strip())) self.assertIn("Push completed", out.getvalue()) def test_failed_add(self): self.init_with_local_catalog() test_dir = os.path.join(self.tmpdir, "test-directory") os.makedirs(test_dir) with self.captured_output() as (out, err): with self.assertRaises(SystemExit) as context: self.run_poco_command("project", "add", test_dir) self.assertIsNotNone(context.exception) self.assertIn("Target directory or parents are not a valid git repository", out.getvalue().strip()) def test_failed_add_without_poco_file(self): self.init_with_local_catalog() test_dir = os.path.join(self.tmpdir, "test-directory") os.makedirs(test_dir) git.Repo.clone_from(url=AbstractTestSuite.STACK_LIST_SAMPLE['nginx']['git'], to_path=test_dir) os.remove(os.path.join(test_dir, 'nginx', 'poco.yml')) with self.captured_output() as (out, err): with self.assertRaises(SystemExit) as context: self.run_poco_command("project", "add", test_dir) self.assertIsNotNone(context.exception) self.assertIn("Directory does not contain Poco file!", out.getvalue().strip()) def test_add_and_remove(self): self.init_with_local_catalog() test_dir = os.path.join(self.tmpdir, "test-directory") os.makedirs(test_dir) git.Repo.clone_from(url=AbstractTestSuite.STACK_LIST_SAMPLE['nginx']['git'], to_path=test_dir) os.rename(os.path.join(test_dir, 'nginx', 'poco.yml'), os.path.join(test_dir, 'poco.yml')) with self.captured_output() as (out, err): self.run_poco_command("project", "add", test_dir) self.assertEqual(0, len(err.getvalue().strip())) self.assertIn("Project added", out.getvalue()) self.clean_states() with self.captured_output() as (out, err): self.run_poco_command("catalog") self.assertEqual(0, len(err.getvalue().strip())) for key in AbstractTestSuite.STACK_LIST_SAMPLE.keys(): self.assertTrue(key in out.getvalue().strip()) self.assertIn("test-directory", out.getvalue()) self.clean_states() with self.captured_output() as (out, err): self.run_poco_command("project", "remove", "test-directory") self.assertEqual(0, len(err.getvalue().strip())) self.assertIn("Project removed", out.getvalue()) self.clean_states() with self.captured_output() as (out, err): self.run_poco_command("catalog") self.assertEqual(0, len(err.getvalue().strip())) for key in AbstractTestSuite.STACK_LIST_SAMPLE.keys(): self.assertTrue(key in out.getvalue().strip()) self.assertNotIn("test-directory", out.getvalue()) def test_init_without_catalog(self): self.init_with_local_catalog() self.assertIsNone(FileUtils.get_file_with_extension('poco', directory=self.ws_dir)) self.assertIsNone(FileUtils.get_file_with_extension('docker-compose', directory=self.ws_dir)) with self.captured_output() as (out, err): self.run_poco_command("project", "init") self.assertEqual(0, len(err.getvalue().strip())) self.assertIsNotNone(FileUtils.get_file_with_extension('poco', directory=self.ws_dir)) self.assertIsNotNone(FileUtils.get_file_with_extension('docker-compose', directory=self.ws_dir)) def test_checkout(self): self.init_with_remote_catalog() base_dir = os.path.join(self.ws_dir, 'poco-example') directory = os.path.join(base_dir, 'nginx') self.assertFalse(os.path.exists(directory)) with self.captured_output() as (out, err): self.run_poco_command("checkout", "nginx") self.assertIn("Project checkout complete " + base_dir, out.getvalue().strip()) self.assertEqual(0, len(err.getvalue().strip())) self.assertTrue(os.path.exists(directory)) def test_install(self): self.init_with_remote_catalog() base_dir = os.path.join(self.ws_dir, 'poco-example') directory = os.path.join(base_dir, 'nginx') self.assertFalse(os.path.exists(directory)) with self.captured_output() as (out, err): self.run_poco_command("install", "nginx") self.assertIn("Install completed to " + base_dir, out.getvalue().strip()) self.assertEqual(0, len(err.getvalue().strip())) self.assertTrue(os.path.exists(directory)) def test_plan_list_with_not_exists_project(self): self.init_with_local_catalog() with self.captured_output() as (out, err): with self.assertRaises(SystemExit) as context: self.run_poco_command("plan", "ls") self.assertIsNotNone(context.exception) self.assertIn("Poco file not found:", out.getvalue()) def test_plan_list(self): self.init_with_remote_catalog() with self.captured_output() as (out, err): self.run_poco_command("plan", "ls", "nginx") self.assertEqual(0, len(err.getvalue())) self.assertIn("default", out.getvalue()) self.assertIn("demo/hello", out.getvalue()) def test_branches(self): self.init_with_local_catalog() with self.captured_output() as (out, err): self.run_poco_command("branches", "nginx") self.assertEqual(0, len(err.getvalue())) self.assertIn("master", out.getvalue()) def test_branch_without_change_branch(self): self.init_with_local_catalog() with self.captured_output() as (out, err): self.run_poco_command("install", "nginx") self.assertIn("Install completed to ", out.getvalue().strip()) self.assertEqual(0, len(err.getvalue().strip())) with self.captured_output() as (out, err): self.run_poco_command("branch", "mysql", "master") self.assertEqual(0, len(err.getvalue())) self.assertIn("Branch changed", out.getvalue())

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23,864

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119

47.632735

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null

0

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e959fbf3a34e846aed8898caa0bb12c15198df12

17,778

py

Python

OpenKapitza/ray_tracing_monte_carlo.py

ariahosseini/OpenKapitza

43df7d4af897ae955ad1e8f19ae45fee851683bb

[ "MIT" ]

4

2022-03-07T02:02:43.000Z

2022-03-18T18:33:01.000Z

OpenKapitza/ray_tracing_monte_carlo.py

ariahosseini/OpenKapitza

43df7d4af897ae955ad1e8f19ae45fee851683bb

[ "MIT" ]

null

OpenKapitza/ray_tracing_monte_carlo.py

ariahosseini/OpenKapitza

43df7d4af897ae955ad1e8f19ae45fee851683bb

[ "MIT" ]

null

""" A Monte Carlo ray tracing model that simulate the auto-correlation heat current process in materials with nanoscale porosity """ from scipy import integrate import numpy as np from .autocorrelation_func import acf, acf_fft time_index = lambda time, max_time, time_steps: int(round((time_steps-1)*time/max_time)) def random_direction(): # A method to pick a random direction for phonon propagation theta = np.arccos(1 - (2*np.random.uniform(0, 1))) # theta is the angle with x in Cartesian coordinates phi = np.random.uniform(-np.pi, np.pi) # phi is the angle with z in Cartesian coordinates return theta, phi def get_random_phonon_spec_wall(tau_max: float, time_intervals: int, v_g: float, tau_mean: float, L: float, P_reflection: float): """ Compute auto-correlation for phonons between walls with spectral scattering :arg tau_max: float Maximum correlation time to compute the ACF out to time_intervals: int Time intervals v_g: float Phonon group velocity (magnitude) tau_mean: float Phonon's average lifetime L: float Spacing between walls P_reflection: float The probability of reflection :returns acf_func: np.ndarray Auto-correlation Int: np.ndarray Intensity """ J = np.zeros([3, time_intervals]) # Initiate heat flux vector time = np.linspace(0, tau_max, time_intervals) # Time theta, phi = random_direction() # Get random direction # Phonon group velocity vector nv = np.array([np.cos(theta), np.sin(theta)*np.cos(phi), np.sin(theta)*np.sin(phi)]) v = v_g * nv direction = float(np.sign(v[0])) # Find the direction along x x = np.random.uniform(0, L) # Get random starting position tau_hit = (L * 0.5 * (1 + direction) - x) / v[0] # Time of flight to the wall hit_index = time_index(tau_hit, tau_max, time_intervals) # Time index of the phonon flight to the wall delta_tau = L/np.abs(v[0]) # Time of flight between walls # Generate random lifetime r_tau = np.random.random() # Random number between 0 and 1 tau_o = -tau_mean * np.log(1 - r_tau) # Phonon annihilation time # Find annihilation time index die_index = min(time_index(tau_o, tau_max, time_intervals), time_intervals) now_index = 0 hit_count = 0 # counters while hit_index < die_index: row = np.ones(hit_index-now_index) J[:, now_index:hit_index] = np.array([v[i]*row for i in range(3)]) hit_count += 1 dice = np.random.random() if dice < P_reflection: direction *= -1.0 v[0] *= -1.0 tau_hit += delta_tau now_index = hit_index hit_index = time_index(tau_hit, tau_max, time_intervals) row = np.ones(die_index-now_index) J[:, now_index:die_index] = np.array([v[i]*row for i in range(3)]) # Heat flux acf_func = acf(time, J) # Auto-correlation Int = np.array([integrate.cumtrapz(acf_func[i], time, initial = 0) for i in range(3)]) # Intensity return acf_func, Int def get_random_phonon_spec_wall_fft(tau_max: float, time_intervals: int, v_g: float, tau_mean: float, L: float, P_reflection: float): """ Compute auto-correlation for phonons between walls with spectral scattering using discrete fourier method :arg tau_max: float Maximum correlation time to compute the ACF out to time_intervals: int Time intervals v_g: float Phonon group velocity (magnitude) tau_mean: float Phonon's average lifetime L: float Spacing between walls P_reflection: float The probability of reflection :returns acf_fft: np.ndarray Auto-correlation Int_fft: np.ndarray Intensity """ J = np.zeros([3, time_intervals]) # Initiate heat flux vector time = np.linspace(0, tau_max, time_intervals) # Time theta, phi = random_direction() # Get random direction # Phonon group velocity vector nv = np.array([np.cos(theta), np.sin(theta)*np.cos(phi), np.sin(theta)*np.sin(phi)]) v = v_g * nv direction = float(np.sign(v[0])) # Find the direction along x # Get random starting position and time of flight to the wall x = np.random.uniform(0, L) # Get random starting position tau_hit = (L * 0.5 *(1 + direction) - x) / v[0] hit_index = time_index(tau_hit, tau_max, time_intervals) # Time index of the phonon flight to the wall delta_tau = L/np.abs(v[0]) # Time of flight between walls r_tau = np.random.random() # Random number between 0 and 1 tau_o = -tau_mean * np.log(1 - r_tau) # Phonon annihilation time # Find annihilation time index die_index = min(time_index(tau_o, tau_max, time_intervals), time_intervals) now_index = 0 hit_count = 0 while hit_index < die_index: row = np.ones(hit_index-now_index) J[:, now_index:hit_index] = np.array([v[i]*row for i in range(3)]) hit_count += 1 dice = np.random.random() if dice < P_reflection: direction *= -1.0 v[0] *= -1.0 tau_hit += delta_tau now_index = hit_index hit_index = time_index(tau_hit, tau_max, time_intervals) row = np.ones(die_index-now_index) J[:, now_index:die_index] = np.array([v[i]*row for i in range(3)]) # Heat flux acf_fft_func = acf_fft(time, J) # Auto-correlation time_ind = (1+(time_intervals-1)/2) # Intensity Int_fft = np.array([integrate.cumtrapz(acf_fft_func[i, :time_ind], time[:time_ind], initial = 0) for i in range(3)]) return acf_fft_func, Int_fft def get_random_phonon_diff_wall(tau_max: float, time_intervals: int, v_g: float, tau_mean: float, L: float, P_reflection: float): """ compute auto-correlation for phonons between walls with diffusive scatting :arg tau_max: float Maximum correlation time to compute the ACF out to time_intervals: int Time intervals v_g: float Phonon group velocity (magnitude) tau_mean: float Phonon's average lifetime L: float Spacing between walls P_reflection: float The probability of reflection :returns acf_func: np.ndarray Auto-correlation Int: np.ndarray Intensity """ J = np.zeros([3, time_intervals]) # Initiate heat flux vector time = np.linspace(0, tau_max, time_intervals) # Time # Get random direction theta, phi = random_direction() # Phonon group velocity vector nv = np.array([np.cos(theta), np.sin(theta)*np.cos(phi), np.sin(theta)*np.sin(phi)]) v = v_g * nv direction = float(np.sign(v[0])) # Find the direction along x x = np.random.uniform(0, L) # Get random starting position and time of flight to the wall tau_hit = (L * 0.5 *(1 + direction) - x) / v[0] # Time of flight to the wall delta_tau = L/np.abs(v[0]) # Time of flight between walls r_tau = np.random.random() # Random number between 0 and 1 tau_o = -tau_mean * np.log(1 - r_tau) # Phonon annihilation time tau_o_ind = int(round((time_intervals-1)*tau_o/tau_max)) max_tau_ind = min(tau_o_ind, time_intervals) for i in range(max_tau_ind): if time[i] >= tau_hit: dice = np.random.random() if dice < P_reflection: direction *= -1.0 theta, phi = random_direction() nv = np.array([np.cos(theta), np.sin(theta)*np.cos(phi), np.sin(theta)*np.sin(phi)]) nv[0] = abs(nv[0])*direction v = v_g * nv delta_tau = L/np.abs(v[0]) # Time of flight between walls tau_hit += delta_tau J[:, i] = v # Heat flux acf_func = acf(time, J) # Auto-correlation # Intensity Int = np.array([integrate.cumtrapz(acf_func[i], time, initial = 0) for i in range(3)]) return acf_func, Int def random_beta_angle(beta_min: float, beta_max: float): return np.arcsin(np.random.random() * (np.sin(beta_max) - np.sin(beta_min))+np.sin(beta_min)) def PT(theta_prime: float, alpha: float): return (np.abs(np.cos(theta_prime)) - alpha)/np.abs(np.cos(theta_prime)) def get_random_phonon_spec_cyli(tau_max: float, time_intervals: int, v_g: float, tau_mean: float, L: float, alpha: float): """ A method to compute auto-correlation for phonons between cylindrical pores with spectral scattering :arg tau_max: float Maximum correlation time to compute the ACF out to time_intervals: int Time intervals v_g: float Phonon group velocity (magnitude) tau_mean: float Phonon's average lifetime L: float Spacing between walls alpha: float The probability of reflection :returns acf_func: np.ndarray Auto-correlation Int: np.ndarray Intensity """ J = np.zeros([3, time_intervals]) # Initiate heat flux vector time = np.linspace(0, tau_max, time_intervals) # Time theta, phi = random_direction() # Get random direction # Phonon group velocity vector nv = np.array([np.cos(theta), np.sin(theta)*np.cos(phi), np.sin(theta)*np.sin(phi)]) v = v_g * nv direction = float(np.sign(v[0])) # Find the direction along x vxz = np.sqrt((v[0])**2 + (v[2])**2) # Phonon group velocity vector theta_prime = np.arctan2(v[2], v[0]) # Phonon group velocity vector angel # Get random starting position and time of flight to the wall x = np.random.uniform(0, L) # Get random starting position tau_hit = (L * 0.5 *(1 + direction) - x) / v[0] # Time of flight to the wall delta_tau = L/np.abs(v[0]) # Time of flight between walls # Get random lifetime r_tau = np.random.random() # Random number between 0 and 1 tau_o = -tau_mean * np.log(1 - r_tau) # Phonon annihilation time reflection = 0 transmitted = 0 tau_o_ind = int(round((time_intervals-1)*tau_o/tau_max)) max_tau_ind = min(tau_o_ind, time_intervals) for i in range(max_tau_ind): if time[i] >= tau_hit: T = PT(theta_prime, alpha) beta_min = -np.pi/2 beta_max = np.pi/2 if T < 0: # We have shadowing and so need to adjust the limits on the # possible incidence angles Beta if np.sin(theta_prime) * np.cos(theta_prime) >= 0: beta_min = np.arcsin(1 - (2 * np.abs(np.cos(theta_prime)))/alpha) else: beta_max = -np.arcsin(1 - (2 * np.abs(np.cos(theta_prime)))/alpha) beta = random_beta_angle(beta_min, beta_max) reflection += 1 else: if np.random.random() < T: # Transmitted beta = np.pi/2 transmitted += 1 else: # Scattered beta = random_beta_angle(beta_min, beta_max) reflection += 1 theta_prime += np.pi - (2*beta) # New direction of travel in the x-z plane v[0] = vxz * np.cos(theta_prime) v[2] = vxz * np.sin(theta_prime) tau_hit += L/np.abs(v[0]) J[:, i] = v # Heat flux acf_func = acf(time, J) # Auto-correlation Int = np.array([integrate.cumtrapz(acf_func[i], time, initial = 0) for i in range(3)]) # Intensity return acf_func, Int def get_random_phonon_diff_cyli(tau_max: float, time_intervals: int, v_g: float, tau_mean: float, L: float, alpha: float): """ compute auto-correlation for phonons between cylindrical pores with diffusive scattering :arg tau_max: float Maximum correlation time to compute the ACF out to time_intervals: int Time intervals v_g: float Phonon group velocity (magnitude) tau_mean: float Phonon's average lifetime L: float Spacing between walls alpha: float The probability of reflection :returns acf_func: np.ndarray Auto-correlation Int: np.ndarray Intensity """ J = np.zeros([3, time_intervals]) # Initiate heat flux vector time = np.linspace(0, tau_max, time_intervals) # Time theta, phi = random_direction() # Get random direction # Phonon group velocity vector nv = np.array([np.cos(theta), np.sin(theta)*np.cos(phi), np.sin(theta)*np.sin(phi)]) v = v_g * nv direction = float(np.sign(v[0])) # Find the direction along x vxz = np.sqrt((v[0])**2 + (v[2])**2) # Phonon group velocity vector theta_prime = np.arctan2(v[2], v[0]) # Phonon group velocity vector angel # Get random starting position and time of flight to the wall x = np.random.uniform(0, L) # Get random starting position tau_hit = (L * 0.5 *(1 + direction) - x) / v[0] # Time of flight to the wall delta_tau = L/np.abs(v[0]) # Time of flight between walls # Get random lifetime r_tau = np.random.random() # Random number between 0 and 1 tau_o = -tau_mean * np.log(1 - r_tau) # Phonon annihilation time reflection = 0 transmitted = 0 # Find annihilation time index tau_o_ind = int(round((time_intervals-1)*tau_o/tau_max)) max_tau_ind = min(tau_o_ind, time_intervals) for i in range(max_tau_ind): if time[i] >= tau_hit: T = PT(theta_prime, alpha) beta_min = -np.pi/2 beta_max = np.pi/2 if T < 0: # We have shadowing and so need to adjust the limits on the # possible incidence angles Beta if np.sin(theta_prime) * np.cos(theta_prime) >= 0: beta_min = np.arcsin(1 - (2 * np.abs(np.cos(theta_prime)))/alpha) else: beta_max = -np.arcsin(1 - (2 * np.abs(np.cos(theta_prime)))/alpha) beta = random_beta_angle(beta_min, beta_max) reflection += 1 else: if np.random.random() < T: # Transmitted beta = np.pi/2 transmitted += 1 else: # Scattered beta = random_beta_angle(beta_min, beta_max) reflection += 1 theta_prime += np.pi - (2*beta) # New direction of travel in the x-z plane v[0] = vxz * np.cos(theta_prime) v[2] = vxz * np.sin(theta_prime) tau_hit += L/np.abs(v[0]) J[:,i] = v # Heat flux acf_func = acf(time, J) # Auto-correlation # Intensity Int = np.array([integrate.cumtrapz(acf_func[i], time, initial = 0) for i in range(3)]) return acf_func, Int def average_phonons(num_blocks: int, samples_per_block: int, tau_max: float, time_intervals: int, v_g: float, tau_mean: float, L: float, alpha: float, mode: str): """ Average over num_blocks of samples_per_block :arg num_blocks: int Number of blocks to average samples_per_block: int Number of samples in each block tau_max: float Maximum correlation time to compute the ACF out to time_intervals: int Time intervals v_g: float Phonon group velocity (magnitude) tau_mean: float Phonon's average lifetime L: float Spacing between walls alpha: float The probability of reflection mode: str Scattering type — SpecWall or SpecWall_fft, DiffWall, SpecCyli, DiffCyli :returns ACFm: np.ndarray Mean of auto-correlation ACFe: np.ndarray Standard deviation of auto-correlation km: np.ndarray Mean of thermal conductivity ke : np.ndarray Standard deviation of thermal conductivity """ ACF = np.zeros([3, num_blocks, time_intervals]) kappa = np.zeros([3, num_blocks, time_intervals]) for i in range(num_blocks): for j in range(samples_per_block): if mode == "SpecWall": acf_func, Int = get_random_phonon_spec_wall(tau_max, time_intervals, v_g, tau_mean, L, alpha) if mode == "SpecWall_fft": acf_func, Int = get_random_phonon_spec_wall(tau_max, time_intervals, v_g, tau_mean, L, alpha) if mode == "DiffWall": acf_func, Int = get_random_phonon_diff_wall(tau_max, time_intervals, v_g, tau_mean, L, alpha) if mode == "SpecCyli": acf_func, Int = get_random_phonon_spec_cyli(tau_max, time_intervals, v_g, tau_mean, L, alpha) if mode == "DiffCyli": acf_func, Int = get_random_phonon_diff_cyli(tau_max, time_intervals, v_g, tau_mean, L, alpha) ACF[:, i] += acf_func kappa[:, i] += Int ACF /= tau_mean*float(samples_per_block) kappa /= tau_mean*float(samples_per_block) ACFm = ACF.mean(axis=1) # Mean of auto-correlation ACFe = ACF.std(axis=1)/np.sqrt(float(num_blocks-1)) # Standard deviation of auto-correlation km = kappa.mean(axis=1) # Mean of thermal conductivity ke = kappa.std(axis=1)/np.sqrt(float(num_blocks-1)) # Standard deviation of thermal conductivity return ACFm, ACFe, km, ke

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null

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7

e95c1d073d8bdea850dff2d10f3b528e06f7568c

2,302

py

Python

neko/modules/mongodb/couples_db.py

itzrexmodz/Carla-1

c775063a0ef0d144649ace6f428c37e6e8d2c092

[ "MIT" ]

4

2021-12-26T11:42:45.000Z

2021-12-27T05:18:17.000Z

neko/modules/mongodb/couples_db.py

itzrexmodz/Carla-1

c775063a0ef0d144649ace6f428c37e6e8d2c092

[ "MIT" ]

null

neko/modules/mongodb/couples_db.py

itzrexmodz/Carla-1

c775063a0ef0d144649ace6f428c37e6e8d2c092

[ "MIT" ]

7

2021-12-26T14:49:37.000Z

2022-01-31T09:32:07.000Z

from neko.modules import db couples = db.couple votes = db.votes_couple_up v_otes = db.votes_couple_down def get_couple(chat_id: int, date: str): _lovers = couples.find_one({"chat_id": chat_id}) if not _lovers: lovers = {} else: lovers = _lovers["couple"] if date in lovers: return lovers[date] else: return False def save_couple(chat_id: int, date: str, couple: dict): _lovers = couples.find_one({"chat_id": chat_id}) if not _lovers: lovers = {} else: lovers = _lovers["couple"] lovers[date] = couple couples.update_one({"chat_id": chat_id}, {"$set": {"couple": lovers}}, upsert=True) def add_vote_up(event_id: int, user_id: int): _votes = votes.find_one({"event_id": event_id}) if not _votes: users = [] else: users = _votes["users"] r = users r.append(user_id) votes.update_one({"event_id": event_id}, {"$set": {"users": r}}, upsert=True) def rm_vote_up(event_id: int, user_id: int): _votes = votes.find_one({"event_id": event_id}) if not _votes: return False else: users = _votes["users"] r = users r.remove(user_id) votes.update_one({"event_id": event_id}, {"$set": {"users": r}}, upsert=True) def voted_up(event_id: int, user_id: int): _votes = votes.find_one({"event_id": event_id}) if not _votes: return False if user_id in _votes["users"]: return True return False def add_vote_down(event_id: int, user_id: int): _votes = v_otes.find_one({"event_id": event_id}) if not _votes: users = [] else: users = _votes["users"] r = users r.append(user_id) v_otes.update_one({"event_id": event_id}, {"$set": {"users": r}}, upsert=True) def rm_vote_down(event_id: int, user_id: int): _votes = v_otes.find_one({"event_id": event_id}) if not _votes: return False else: users = _votes["users"] r = users r.remove(user_id) v_otes.update_one({"event_id": event_id}, {"$set": {"users": r}}, upsert=True) def voted_down(event_id: int, user_id: int): _votes = v_otes.find_one({"event_id": event_id}) if not _votes: return False if user_id in _votes["users"]: return True return False

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1

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null

0

7

75c97e5eae3217dec80fa3c9cbee0236eee7bcc8

2,874

py

Python

notes/None.py

andrewtruong/notes

24e3a7d822f746ac4ab6c3186bc44dccb4f0e169

[ "Apache-2.0" ]

null

notes/None.py

andrewtruong/notes

24e3a7d822f746ac4ab6c3186bc44dccb4f0e169

[ "Apache-2.0" ]

null

notes/None.py

andrewtruong/notes

24e3a7d822f746ac4ab6c3186bc44dccb4f0e169

[ "Apache-2.0" ]

null

# Cell import httpx import re from pathlib import Path from tqdm.auto import tqdm from fastcore.all import typedispatch # from notes.asyncio import async_map # Cell import httpx import re from pathlib import Path from tqdm.auto import tqdm from fastcore.all import typedispatch # from notes.asyncio import async_map # Cell import httpx import re from pathlib import Path from tqdm.auto import tqdm from fastcore.all import typedispatch # from notes.asyncio import async_map # Cell import httpx import re from pathlib import Path from tqdm.auto import tqdm from fastcore.all import typedispatch # from notes.asyncio import async_map # Cell import httpx import re from pathlib import Path from tqdm.auto import tqdm from fastcore.all import typedispatch # from notes.asyncio import async_map # Cell import httpx import re from pathlib import Path from tqdm.auto import tqdm from fastcore.all import typedispatch # from notes.asyncio import async_map # Cell import httpx import re from pathlib import Path from tqdm.auto import tqdm from fastcore.all import typedispatch # from notes.asyncio import async_map # Cell import httpx import re from pathlib import Path from tqdm.auto import tqdm from fastcore.all import typedispatch # from notes.asyncio import async_map # Cell import httpx import re from pathlib import Path from tqdm.auto import tqdm from fastcore.all import typedispatch # from notes.asyncio import async_map # Cell import httpx import re from pathlib import Path from tqdm.auto import tqdm from fastcore.all import typedispatch # from notes.asyncio import async_map # Cell import httpx import re from pathlib import Path from tqdm.auto import tqdm from fastcore.all import typedispatch # from notes.asyncio import async_map # Cell import httpx import re from pathlib import Path from tqdm.auto import tqdm from fastcore.all import typedispatch # from notes.asyncio import async_map # Cell import httpx import re from pathlib import Path from tqdm.auto import tqdm from fastcore.all import typedispatch # from notes.asyncio import async_map # Cell import httpx import re from pathlib import Path from tqdm.auto import tqdm from fastcore.all import typedispatch # from notes.asyncio import async_map # Cell import lightgbm as lgb import pandas as pd from .pandas import categorize from sklearn.metrics import mean_squared_error as mse from sklearn.model_selection import train_test_split import optuna import wandb # Cell import lightgbm as lgb import pandas as pd from .pandas import categorize from sklearn.metrics import mean_squared_error as mse from sklearn.model_selection import train_test_split import optuna import wandb # Cell import lightgbm as lgb import pandas as pd from .pandas import categorize from sklearn.metrics import mean_squared_error as mse from sklearn.model_selection import train_test_split import optuna import wandb

20.528571

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1

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null

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1

0

1

0

1

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10

75e3c0949809108f8c8467cae4110f140d3cd12a

191

py

Python

datatools_bdh/all.py

sfu-bigdata/datatools-bdh

43303db2e165c10b43f5afe5293d41e655a05040

[ "MIT" ]

null

datatools_bdh/all.py

sfu-bigdata/datatools-bdh

43303db2e165c10b43f5afe5293d41e655a05040

[ "MIT" ]

null

datatools_bdh/all.py

sfu-bigdata/datatools-bdh

43303db2e165c10b43f5afe5293d41e655a05040

[ "MIT" ]

null

from datatools_bdh.ipython import * from datatools_bdh.plot import * import datatools_bdh.pccf as pccf from datatools_bdh.utils import * from .pandas_utils import * from .dict_utils import *

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191

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true

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1

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null

0

1

0

1

0

1

0

7

2f028d0e500844923fdb9ca91594a416ae369714

148

py

Python

tests/test_connect.py

swimmio/sqlalchemy_swimm

d24accb7792743cf586bd7062531d108e7063eba

[ "MIT" ]

null

tests/test_connect.py

swimmio/sqlalchemy_swimm

d24accb7792743cf586bd7062531d108e7063eba

[ "MIT" ]

null

tests/test_connect.py

swimmio/sqlalchemy_swimm

d24accb7792743cf586bd7062531d108e7063eba

[ "MIT" ]

null

from src import connect def test_connect_to_helloworldb() -> None: assert sorted(connect.connect_to_helloworldb()) == ['hello', 'sqlalchemy']

24.666667

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5.833333

0.722222

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0.380952

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null

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1

0

1

0

1

0

7

f97586da20c80812e979110a9e97665989b13849

166

py

Python

hyperglass_bird/__init__.py

AS207960/hyperglass-bird

53e93ffa7a11636c1ee1b4a1d2a6e1dcd1ad7de9

[ "BSD-3-Clause-Clear" ]

2

2019-06-24T04:02:27.000Z

2020-06-09T00:36:34.000Z

hyperglass_bird/__init__.py

AS207960/hyperglass-bird

53e93ffa7a11636c1ee1b4a1d2a6e1dcd1ad7de9

[ "BSD-3-Clause-Clear" ]

null

hyperglass_bird/__init__.py

AS207960/hyperglass-bird

53e93ffa7a11636c1ee1b4a1d2a6e1dcd1ad7de9

[ "BSD-3-Clause-Clear" ]

1

2020-01-23T10:20:46.000Z

"""hyperglass_bird is a BIRD API designed for use with the Hyperglass looking glass""" from hyperglass_bird import execute from hyperglass_bird import configuration

33.2

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0

8

f98a5c79fd15b092b14dfa3d7b3eb40e7dddb420

3,941

py

Python

backend/apps/iamstudent/migrations/0007_auto_20200402_2055.py

n-hackert/match4healthcare

761248c27b49e568c545c643a72eac9a040649d7

[ "MIT" ]

2

2020-03-28T13:56:39.000Z

2020-03-29T10:16:12.000Z

backend/apps/iamstudent/migrations/0007_auto_20200402_2055.py

n-hackert/match4healthcare

761248c27b49e568c545c643a72eac9a040649d7

[ "MIT" ]

76

2020-03-27T21:53:04.000Z

2020-03-30T20:27:43.000Z

backend/apps/iamstudent/migrations/0007_auto_20200402_2055.py

n-hackert/match4healthcare

761248c27b49e568c545c643a72eac9a040649d7

[ "MIT" ]

null

# Generated by Django 3.0.4 on 2020-04-02 20:55 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('iamstudent', '0006_merge_20200330_0313'), ] operations = [ migrations.AddField( model_name='student', name='ausbildung_typ_ata', field=models.BooleanField(default=False), ), migrations.AddField( model_name='student', name='ausbildung_typ_ata_abschnitt', field=models.IntegerField(choices=[(0, 'Keine Angabe'), (1, '1. Jahr'), (2, '2. Jahr'), (3, '3. Jahr'), (4, 'Berufstätig')], default=0, null=True), ), migrations.AddField( model_name='student', name='ausbildung_typ_ergotherapie', field=models.BooleanField(default=False), ), migrations.AddField( model_name='student', name='ausbildung_typ_ergotherapie_abschnitt', field=models.IntegerField(choices=[(0, 'Keine Angabe'), (1, 'In Ausbildung'), (2, 'Berufstätig')], default=0, null=True), ), migrations.AddField( model_name='student', name='ausbildung_typ_ota', field=models.BooleanField(default=False), ), migrations.AddField( model_name='student', name='ausbildung_typ_ota_abschnitt', field=models.IntegerField(choices=[(0, 'Keine Angabe'), (1, '1. Jahr'), (2, '2. Jahr'), (3, '3. Jahr'), (4, 'Berufstätig')], default=0, null=True), ), migrations.AddField( model_name='student', name='ausbildung_typ_psycho', field=models.BooleanField(default=False), ), migrations.AddField( model_name='student', name='ausbildung_typ_psycho_abschnitt', field=models.IntegerField(choices=[(0, 'Keine Angabe'), (1, 'Studium'), (2, 'In Ausbildung'), (3, 'Berufstätig')], default=0, null=True), ), migrations.AddField( model_name='studentlistfiltermodel', name='ausbildung_typ_ata', field=models.NullBooleanField(default=None), ), migrations.AddField( model_name='studentlistfiltermodel', name='ausbildung_typ_ata_abschnitt_x_gt', field=models.IntegerField(default=0), ), migrations.AddField( model_name='studentlistfiltermodel', name='ausbildung_typ_ata_abschnitt_x_lt', field=models.IntegerField(default=0), ), migrations.AddField( model_name='studentlistfiltermodel', name='ausbildung_typ_ergotherapie', field=models.NullBooleanField(default=None), ), migrations.AddField( model_name='studentlistfiltermodel', name='ausbildung_typ_ota', field=models.NullBooleanField(default=None), ), migrations.AddField( model_name='studentlistfiltermodel', name='ausbildung_typ_ota_abschnitt_x_gt', field=models.IntegerField(default=0), ), migrations.AddField( model_name='studentlistfiltermodel', name='ausbildung_typ_ota_abschnitt_x_lt', field=models.IntegerField(default=0), ), migrations.AddField( model_name='studentlistfiltermodel', name='ausbildung_typ_psycho', field=models.NullBooleanField(default=None), ), migrations.AddField( model_name='studentlistfiltermodel', name='ausbildung_typ_psycho_abschnitt_x_gt', field=models.IntegerField(default=0), ), migrations.AddField( model_name='studentlistfiltermodel', name='ausbildung_typ_psycho_abschnitt_x_lt', field=models.IntegerField(default=0), ), ]

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f9911d1a09547b8aafb12a908dc9507f72b7ef60

169

py

Python

Pseudo_Goldstone/Get_Feynman_Rules/__init__.py

dkaramit/pseudo-Goldstone_DM

70fbb4ad4be190226d230a20dfb19b804e15aae6

[ "MIT" ]

null

Pseudo_Goldstone/Get_Feynman_Rules/__init__.py

dkaramit/pseudo-Goldstone_DM

70fbb4ad4be190226d230a20dfb19b804e15aae6

[ "MIT" ]

null

Pseudo_Goldstone/Get_Feynman_Rules/__init__.py

dkaramit/pseudo-Goldstone_DM

70fbb4ad4be190226d230a20dfb19b804e15aae6

[ "MIT" ]

null

__all__=['Make_Feynman_Rules','VertexValue','CheckInteractions','StoreVert'] from Get_Feynman_Rules import Make_Feynman_Rules,VertexValue,CheckInteractions,StoreVert

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7

f991c436cc2a0d40d1d54db0b2de696809282cf3

125

py

Python

tnt/optimizers/__init__.py

BigFishMaster/tnt

8b80bb3b194eb87ac18924428ef0924c2fb263c5

[ "BSD-3-Clause" ]

3

2020-12-18T08:50:47.000Z

2020-12-18T08:50:55.000Z

tnt/optimizers/__init__.py

BigFishMaster/tnt

8b80bb3b194eb87ac18924428ef0924c2fb263c5

[ "BSD-3-Clause" ]

5

2021-03-19T11:49:52.000Z

2022-03-12T00:21:18.000Z

tnt/optimizers/__init__.py

BigFishMaster/tnt

8b80bb3b194eb87ac18924428ef0924c2fb263c5

[ "BSD-3-Clause" ]

1

2021-04-20T04:36:40.000Z

from torch.optim import SGD from torch.optim import Adam from torch.optim import RMSprop from .lr_strategy import LRStrategy

25

35

0.84

20

125

5.2

0.5

0.259615

0.403846

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125

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8

f9e622901a971754bd8c9c9fadb23ea2d5be2d50

970

py

Python

src/main/python/apiconnector.py

anj2b/autotwipy

7ace2a2c7738c76acf9698c05eb467a1ea1e05f9

[ "MIT" ]

1

2021-02-09T19:41:44.000Z

src/main/python/apiconnector.py

anj2b/autotwipy

7ace2a2c7738c76acf9698c05eb467a1ea1e05f9

[ "MIT" ]

null

src/main/python/apiconnector.py

anj2b/autotwipy

7ace2a2c7738c76acf9698c05eb467a1ea1e05f9

[ "MIT" ]

null

import time import tweepy class ApiConnector: def __init__(self, one, two, three, four): self.consumer_key = one self.consumer_secret = two self.access_token = three self.access_token_secret = four self.auth = tweepy.OAuthHandler(self.consumer_key, self.consumer_secret) self.auth.set_access_token(self.access_token, self.access_token_secret) self.api = tweepy.API(self.auth) try: self.me = self.api.me() except: raise ("Error") def add_keys(self, one, two, three, four): self.consumer_key = one self.consumer_secret = two self.access_token = three self.access_token_secret = four self.auth = tweepy.OAuthHandler(self.consumer_key, self.consumer_secret) self.auth.set_access_token(self.access_token, self.access_token_secret) self.api = tweepy.API(self.auth) me = self.api.me() return me

30.3125

80

0.645361

126

970

4.738095

0.230159

0.184255

0.201005

0.140704

0.81742

0

0.261856

970

31

81

31.290323

0.833799

0

0.56

0

0.00516

0

1

0.08

false

0

0.08

0

0.24

0

null

0

1

0

1

0

null

0

7

ddbc1d270367fc980eaa416dbc47c82939377500

105

py

Python

Game/Framework/__init__.py

intxparts/LudumDare34

41673bf751dab1562e8f9ccfbcebda80ba79b722

[ "MIT" ]

null

Game/Framework/__init__.py

intxparts/LudumDare34

41673bf751dab1562e8f9ccfbcebda80ba79b722

[ "MIT" ]

null

Game/Framework/__init__.py

intxparts/LudumDare34

41673bf751dab1562e8f9ccfbcebda80ba79b722

[ "MIT" ]

null

from Game.Framework.Game import * from Game.Framework.Scene import * from Game.Framework.Vector import *

26.25

35

0.8

15

105

5.6

0.4

0.285714

0.607143

0.547619

0

0.114286

105

3

36

35

0.903226

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

8

fb3cdd89861a908206b1855f17da6da4fbe993b1

4,443

py

Python

testing/tests.py

maorshutman/bigint

fcadc3e0c59e5fd9cc9f1e8cd377a764093aaa56

[ "MIT" ]

null

testing/tests.py

maorshutman/bigint

fcadc3e0c59e5fd9cc9f1e8cd377a764093aaa56

[ "MIT" ]

null

testing/tests.py

maorshutman/bigint

fcadc3e0c59e5fd9cc9f1e8cd377a764093aaa56

[ "MIT" ]

null

import unittest import mpint # TODO: How to use constants from mpint correctly ? class TestMPInt(unittest.TestCase): def test_new(self): x = mpint.MPInt([1, 1, 0], bits=mpint._MP_PREC) self.assertEqual(x.used, 3) n = 456737 x = mpint.MPInt(n, bits=2*mpint._MP_PREC) self.assertEqual(x.used, 19) y = mpint.MPInt(int(-1), bits=mpint._MP_PREC) self.assertEqual(y.sign, mpint._MP_NEG) z = mpint.MPInt(int(0), bits=mpint._MP_PREC) self.assertEqual(z.sign, mpint._MP_ZPOS) w = mpint.MPInt([0, 0, 0, 1, 1, 0, 1, 1, 1], bits=mpint._MP_PREC) self.assertEqual(w.used, 6) self.assertEqual(w.alloc, mpint._MP_PREC) def test_mp_grow(self): x = mpint.MPInt([1, 1, 0], bits=mpint._MP_PREC) x.mp_grow(31) self.assertEqual(x.shape[1], 32) x = mpint.MPInt([1, 1, 0], bits=mpint._MP_PREC) x.mp_grow(33) self.assertEqual(x.shape[1], 96) def test_mp_clamp(self): x = mpint.MPInt([1, 1, 0], bits=mpint._MP_PREC) x.mp_clamp() self.assertEqual(x.used, 3) x = mpint.MPInt([0, 0, 0, 1, 0, 0, 1, 1, 0], bits=mpint._MP_PREC) x.mp_clamp() self.assertEqual(x.used, 6) def test_mp_copy(self): x = mpint.MPInt([1, 1, 0], bits=mpint._MP_PREC) w = mpint.MPInt([0, 1, 1, 0, 1], bits=mpint._MP_PREC) w.mp_copy(x) self.assertEqual(w.used, 3) n = 456737 # 19 used bits, 0b1101111100000100001 x = mpint.MPInt(n, bits=2*mpint._MP_PREC) w = mpint.MPInt([0, 1, 1, 0, 1], bits=mpint._MP_PREC) w.mp_copy(x) self.assertEqual(w.used, 19) self.assertEqual(w.alloc, 2*mpint._MP_PREC) def test_mp_zero(self): c = mpint.MPInt(int(-234), bits=mpint._MP_PREC) c.mp_zero() self.assertEqual(c.used, 0) self.assertEqual(c.alloc, mpint._MP_PREC) self.assertEqual(c.sign, mpint._MP_ZPOS) def test_mp_abs(self): y = mpint.MPInt(int(-1), bits=mpint._MP_PREC) y_abs = y.mp_abs() self.assertEqual(y_abs.sign, mpint._MP_ZPOS) def test_mp_neg(self): y = mpint.MPInt(int(-1), bits=mpint._MP_PREC) y_abs = y.mp_neg() self.assertEqual(y_abs.sign, mpint._MP_ZPOS) y = mpint.MPInt(int(1), bits=mpint._MP_PREC) y_abs = y.mp_neg() self.assertEqual(y_abs.sign, mpint._MP_NEG) y = mpint.MPInt(0, bits=mpint._MP_PREC) y_abs = y.mp_neg() self.assertEqual(y_abs.sign, mpint._MP_ZPOS) def test_mp_cmp_mag(self): x = mpint.MPInt(int(-234), bits=mpint._MP_PREC) y = mpint.MPInt(int(-234), bits=mpint._MP_PREC) self.assertEqual(mpint.MPInt.mp_cmp_mag(x, y), mpint._MP_EQ) x = mpint.MPInt(int(-15), bits=mpint._MP_PREC) y = mpint.MPInt(int(-234), bits=mpint._MP_PREC) self.assertEqual(mpint.MPInt.mp_cmp_mag(x, y), mpint._MP_LT) x = mpint.MPInt(int(234), bits=mpint._MP_PREC) y = mpint.MPInt(int(-234), bits=mpint._MP_PREC) self.assertEqual(mpint.MPInt.mp_cmp_mag(x, y), mpint._MP_EQ) x = mpint.MPInt(0, bits=mpint._MP_PREC) y = mpint.MPInt(int(-0), bits=mpint._MP_PREC) self.assertEqual(mpint.MPInt.mp_cmp_mag(x, y), mpint._MP_EQ) x = mpint.MPInt(456737, bits=2*mpint._MP_PREC) y = mpint.MPInt(456736, bits=2*mpint._MP_PREC) self.assertEqual(mpint.MPInt.mp_cmp_mag(x, y), mpint._MP_GT) def test_mp_cmp(self): x = mpint.MPInt(int(-234), bits=mpint._MP_PREC) y = mpint.MPInt(int(-234), bits=mpint._MP_PREC) self.assertEqual(mpint.MPInt.mp_cmp(x, y), mpint._MP_EQ) x = mpint.MPInt(int(-15), bits=mpint._MP_PREC) y = mpint.MPInt(int(-234), bits=mpint._MP_PREC) self.assertEqual(mpint.MPInt.mp_cmp(x, y), mpint._MP_GT) x = mpint.MPInt(int(234), bits=mpint._MP_PREC) y = mpint.MPInt(int(-234), bits=mpint._MP_PREC) self.assertEqual(mpint.MPInt.mp_cmp(x, y), mpint._MP_GT) x = mpint.MPInt(0, bits=mpint._MP_PREC) y = mpint.MPInt(int(-0), bits=mpint._MP_PREC) self.assertEqual(mpint.MPInt.mp_cmp(x, y), mpint._MP_EQ) x = mpint.MPInt(456737, bits=2*mpint._MP_PREC) y = mpint.MPInt(456736, bits=2*mpint._MP_PREC) self.assertEqual(mpint.MPInt.mp_cmp(x, y), mpint._MP_GT) if __name__ == '__main__': unittest.main()

34.984252

73

0.612424

725

4,443

3.510345

0.085517

0.187033

0.17721

0.188605

0.845973

0.814931

0.788212

0.74499

0.728487

0.699018

0

0.051486

0.234976

4,443

126

74

35.261905

0.697264

0.019131

0

0.568421

0

0.001837

0

0.007937

0.315789

1

0.094737

false

0

0.021053

0

0.126316

0

null

0

1

0

null

0

7

34cee329902eb66855e50f793ab88e93d4d2c82c

11,968

py

Python

easygraph/functions/drawing/drawing.py

easy-graph/Easy-Graph

34dd39e78ff09fb5a68cba7581b81033fd3cc147

[ "BSD-3-Clause" ]

41

2020-09-26T13:44:07.000Z

2022-03-19T08:57:45.000Z

easygraph/functions/drawing/drawing.py

easy-graph/Easy-Graph

34dd39e78ff09fb5a68cba7581b81033fd3cc147

[ "BSD-3-Clause" ]

14

2020-09-26T03:29:08.000Z

2022-03-29T02:47:17.000Z

easygraph/functions/drawing/drawing.py

easy-graph/Easy-Graph

34dd39e78ff09fb5a68cba7581b81033fd3cc147

[ "BSD-3-Clause" ]

8

2020-09-27T08:10:56.000Z

2022-03-29T08:48:16.000Z

import easygraph as eg import matplotlib.pyplot as plt import numpy as np import random __all__=[ "draw_SHS_center", "draw_SHS_center_kk", "draw_kamada_kawai" ] def draw_SHS_center(G,SHS,rate=1,style="side"): """ Draw the graph whose the SH Spanners are in the center, with random layout. Parameters ---------- G : graph A easygraph graph. SHS : list The SH Spanners in graph G. rate : float The proportion of visible points and edges to the total style : stirng "side"- the label is next to the dot "center"- the label is in the center of the dot Returns ------- graph : network the graph whose the SH Spanners are in the center. """ pos=eg.random_position(G) center=np.zeros((len(SHS),2),float) node=np.zeros((len(pos)-len(SHS),2),float) m,n=0,0 if rate==1: for i in pos: if i in SHS: center[n][0]=0.5+(-1)**random.randint(1,2)*pos[i][0]/5 center[n][1]=0.5+(-1)**random.randint(1,2)*pos[i][1]/5 pos[i][0]=center[n][0] pos[i][1]=center[n][1] n+=1 else: node[m][0]=pos[i][0] node[m][1]=pos[i][1] m+=1 if style=='side': plt.scatter(node[:,0], node[:,1], marker = '.', color = 'b', s=10) plt.scatter(center[:,0], center[:,1], marker = '*', color = 'r', s=20) elif style=='center': plt.scatter(node[:,0], node[:,1], marker = 'o', color='None',edgecolors = 'b', s=50,linewidth=0.5) plt.scatter(center[:,0], center[:,1], marker = 'o', color='None',edgecolors = 'r', s=50,linewidth=0.5) k=0 for i in pos: if style=='side': plt.text(pos[i][0], pos[i][1], i, fontsize=5, verticalalignment="top", horizontalalignment="right") elif style=='center': plt.text(pos[i][0], pos[i][1], i, fontsize=5, verticalalignment="center", horizontalalignment="center") k+=1 for i in G.edges: p1=[pos[i[0]][0],pos[i[1]][0]] p2=[pos[i[0]][1],pos[i[1]][1]] plt.plot(p1,p2, 'k-',alpha=0.3,linewidth=0.5) plt.show() else: degree=G.degree() sorted_degree=sorted(degree.items(), key=lambda d: d[1],reverse=True) l=int(rate*len(G)) s=[] for i in sorted_degree: if len(s)<l: s.append(i[0]) for i in pos: if i in SHS and i in s: center[n][0]=0.5+(-1)**random.randint(1,2)*pos[i][0]/5 center[n][1]=0.5+(-1)**random.randint(1,2)*pos[i][1]/5 pos[i][0]=center[n][0] pos[i][1]=center[n][1] n+=1 elif i in s: node[m][0]=pos[i][0] node[m][1]=pos[i][1] m+=1 node=node[0:m,:] center=center[0:n,:] if style=='side': plt.scatter(node[:,0], node[:,1], marker = '.', color = 'b', s=10) plt.scatter(center[:,0], center[:,1], marker = '*', color = 'r', s=20) elif style=='center': plt.scatter(node[:,0], node[:,1], marker = 'o', color='None',edgecolors = 'b', s=50,linewidth=0.5) plt.scatter(center[:,0], center[:,1], marker = 'o', color='None',edgecolors = 'r', s=50,linewidth=0.5) k=0 for i in pos: if i in s: if style=='side': plt.text(pos[i][0], pos[i][1], i, fontsize=5, verticalalignment="top", horizontalalignment="right") elif style=='center': plt.text(pos[i][0], pos[i][1], i, fontsize=5, verticalalignment="center", horizontalalignment="center") k+=1 for i in G.edges: (u,v,t)=i if u in s and v in s: p1=[pos[i[0]][0],pos[i[1]][0]] p2=[pos[i[0]][1],pos[i[1]][1]] plt.plot(p1,p2, 'k-',alpha=0.3,linewidth=0.5) plt.show() return def draw_SHS_center_kk(G,SHS,rate=1,style="side"): """ Draw the graph whose the SH Spanners are in the center, with a Kamada-Kawai force-directed layout. Parameters ---------- G : graph A easygraph graph. SHS : list The SH Spanners in graph G. rate : float The proportion of visible points and edges to the total style : stirng "side"- the label is next to the dot "center"- the label is in the center of the dot Returns ------- graph : network the graph whose the SH Spanners are in the center. """ pos=eg.kamada_kawai_layout(G) center=np.zeros((len(SHS),2),float) node=np.zeros((len(pos)-len(SHS),2),float) m,n=0,0 if rate==1: for i in pos: if i in SHS: center[n][0]=pos[i][0]/5 center[n][1]=pos[i][1]/5 pos[i][0]=center[n][0] pos[i][1]=center[n][1] n+=1 else: node[m][0]=pos[i][0] node[m][1]=pos[i][1] m+=1 if style=='side': plt.scatter(node[:,0], node[:,1], marker = '.', color = 'b', s=10) plt.scatter(center[:,0], center[:,1], marker = '*', color = 'r', s=20) elif style=='center': plt.scatter(node[:,0], node[:,1], marker = 'o', color='None',edgecolors = 'b', s=50,linewidth=0.5) plt.scatter(center[:,0], center[:,1], marker = 'o', color='None',edgecolors = 'r', s=50,linewidth=0.5) k=0 for i in pos: if style=='side': plt.text(pos[i][0], pos[i][1], i, fontsize=5, verticalalignment="top", horizontalalignment="right") elif style=='center': plt.text(pos[i][0], pos[i][1], i, fontsize=5, verticalalignment="center", horizontalalignment="center") k+=1 for i in G.edges: p1=[pos[i[0]][0],pos[i[1]][0]] p2=[pos[i[0]][1],pos[i[1]][1]] plt.plot(p1,p2, 'k-',alpha=0.3,linewidth=0.5) plt.show() else: degree=G.degree() sorted_degree=sorted(degree.items(), key=lambda d: d[1],reverse=True) l=int(rate*len(G)) s=[] for i in sorted_degree: if len(s)<l: s.append(i[0]) for i in pos: if i in SHS and i in s: center[n][0]=pos[i][0]/5 center[n][1]=pos[i][1]/5 pos[i][0]=center[n][0] pos[i][1]=center[n][1] n+=1 elif i in s: node[m][0]=pos[i][0] node[m][1]=pos[i][1] m+=1 node=node[0:m,:] center=center[0:n,:] if style=='side': plt.scatter(node[:,0], node[:,1], marker = '.', color = 'b', s=10) plt.scatter(center[:,0], center[:,1], marker = '*', color = 'r', s=20) elif style=='center': plt.scatter(node[:,0], node[:,1], marker = 'o', color='None',edgecolors = 'b', s=50,linewidth=0.5) plt.scatter(center[:,0], center[:,1], marker = 'o', color='None',edgecolors = 'r', s=50,linewidth=0.5) k=0 for i in pos: if i in s: if style=='side': plt.text(pos[i][0], pos[i][1], i, fontsize=5, verticalalignment="top", horizontalalignment="right") elif style=='center': plt.text(pos[i][0], pos[i][1], i, fontsize=5, verticalalignment="center", horizontalalignment="center") k+=1 for i in G.edges: (u,v,t)=i if u in s and v in s: p1=[pos[i[0]][0],pos[i[1]][0]] p2=[pos[i[0]][1],pos[i[1]][1]] plt.plot(p1,p2, 'k-',alpha=0.3,linewidth=0.5) plt.show() return def draw_kamada_kawai(G,rate=1,style="side"): """Draw the graph G with a Kamada-Kawai force-directed layout. Parameters ---------- G : graph A networkx graph rate : float The proportion of visible points and edges to the total style : stirng "side"- the label is next to the dot "center"- the label is in the center of the dot """ pos=eg.kamada_kawai_layout(G) node=np.zeros((len(pos),2),float) m,n=0,0 if rate==1: for i in pos: node[m][0]=pos[i][0] node[m][1]=pos[i][1] m+=1 if style=='side': plt.scatter(node[:,0], node[:,1], marker = '.', color = 'b', s=10) elif style=='center': plt.scatter(node[:,0], node[:,1], marker = 'o', color='None',edgecolors = 'b', s=50,linewidth=0.5) k=0 for i in pos: if style=='side': plt.text(pos[i][0], pos[i][1], i, fontsize=5, verticalalignment="top", horizontalalignment="right") elif style=='center': plt.text(pos[i][0], pos[i][1], i, fontsize=5, verticalalignment="center", horizontalalignment="center") k+=1 for i in G.edges: p1=[pos[i[0]][0],pos[i[1]][0]] p2=[pos[i[0]][1],pos[i[1]][1]] plt.plot(p1,p2, 'k-',alpha=0.3,linewidth=0.5) plt.show() else: degree=G.degree() sorted_degree=sorted(degree.items(), key=lambda d: d[1],reverse=True) l=int(rate*len(G)) s=[] for i in sorted_degree: if len(s)<l: s.append(i[0]) for i in pos: if i in s: node[m][0]=pos[i][0] node[m][1]=pos[i][1] m+=1 node=node[0:m,:] if style=='side': plt.scatter(node[:,0], node[:,1], marker = '.', color = 'b', s=10) elif style=='center': plt.scatter(node[:,0], node[:,1], marker = 'o', color='None',edgecolors = 'b', s=50,linewidth=0.5) k=0 for i in pos: if i in s: if style=='side': plt.text(pos[i][0], pos[i][1], i, fontsize=5, verticalalignment="top", horizontalalignment="right") elif style=='center': plt.text(pos[i][0], pos[i][1], i, fontsize=5, verticalalignment="center", horizontalalignment="center") k+=1 for i in G.edges: (u,v,t)=i if u in s and v in s: p1=[pos[i[0]][0],pos[i[1]][0]] p2=[pos[i[0]][1],pos[i[1]][1]] plt.plot(p1,p2, 'k-',alpha=0.3,linewidth=0.5) plt.show() return if __name__ == '__main__': G = eg.datasets.get_graph_karateclub() draw_SHS_center(G,[1,33,34],style='side') draw_SHS_center(G,[1,33,34],style='center') draw_SHS_center_kk(G,[1,33,34],style='side') draw_SHS_center_kk(G,[1,33,34],style='center') draw_kamada_kawai(G,style='side') draw_kamada_kawai(G,style='center') draw_SHS_center(G,[1,33,34],rate=0.8,style='side') draw_SHS_center(G,[1,33,34],rate=0.8,style='center') draw_SHS_center_kk(G,[1,33,34],rate=0.8,style='side') draw_SHS_center_kk(G,[1,33,34],rate=0.8,style='center') draw_kamada_kawai(G,rate=0.8,style='side') draw_kamada_kawai(G,rate=0.8,style='center')

34.994152

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11,968

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false

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null

0

1

0

1

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null

0

7

34f7003a4f1b9c88bde231a448aead37a104fea2

634,944

py

Python

out-genfiles/proto/stu3/uscore_pb2.py

rasalt/fhir-datalab

3e329fc8b4226d3e3a4a7c23c306a86e7a9ea0de

[ "Apache-2.0" ]

null

out-genfiles/proto/stu3/uscore_pb2.py

rasalt/fhir-datalab

3e329fc8b4226d3e3a4a7c23c306a86e7a9ea0de

[ "Apache-2.0" ]

null

out-genfiles/proto/stu3/uscore_pb2.py

rasalt/fhir-datalab

3e329fc8b4226d3e3a4a7c23c306a86e7a9ea0de

[ "Apache-2.0" ]

null

# Generated by the protocol buffer compiler. DO NOT EDIT! # source: proto/stu3/uscore.proto import sys _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1')) from google.protobuf import descriptor as _descriptor from google.protobuf import message as _message from google.protobuf import reflection as _reflection from google.protobuf import symbol_database as _symbol_database # @@protoc_insertion_point(imports) _sym_db = _symbol_database.Default() from proto.stu3 import annotations_pb2 as proto_dot_stu3_dot_annotations__pb2 from proto.stu3 import codes_pb2 as proto_dot_stu3_dot_codes__pb2 from proto.stu3 import datatypes_pb2 as proto_dot_stu3_dot_datatypes__pb2 from proto.stu3 import metadatatypes_pb2 as proto_dot_stu3_dot_metadatatypes__pb2 from proto.stu3 import resources_pb2 as proto_dot_stu3_dot_resources__pb2 from proto.stu3 import uscore_codes_pb2 as proto_dot_stu3_dot_uscore__codes__pb2 DESCRIPTOR = _descriptor.FileDescriptor( name='proto/stu3/uscore.proto', package='google.fhir.stu3.uscore', 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full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.Onset', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='date_time', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.Onset.date_time', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='age', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.Onset.age', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='period', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.Onset.period', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='range', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.Onset.range', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='string_value', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.Onset.string_value', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, json_name='string', file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name='onset', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.Onset.onset', index=0, containing_type=None, fields=[]), ], serialized_start=2052, serialized_end=2329, ) _USCOREALLERGYINTOLERANCE_REACTION = _descriptor.Descriptor( name='Reaction', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.Reaction', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.Reaction.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.Reaction.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.Reaction.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='substance', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.Reaction.substance', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='manifestation', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.Reaction.manifestation', index=4, number=5, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='description', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.Reaction.description', index=5, number=6, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='onset', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.Reaction.onset', index=6, number=7, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='severity', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.Reaction.severity', index=7, number=8, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='exposure_route', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.Reaction.exposure_route', index=8, number=9, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='note', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.Reaction.note', index=9, number=10, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=2332, serialized_end=2926, ) _USCOREALLERGYINTOLERANCE = _descriptor.Descriptor( name='UsCoreAllergyintolerance', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='meta', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.meta', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='implicit_rules', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.implicit_rules', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='language', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.language', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='text', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.text', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='contained', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.contained', index=5, number=6, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.extension', index=6, number=7, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.modifier_extension', index=7, number=8, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='identifier', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.identifier', index=8, number=9, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='clinical_status', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.clinical_status', index=9, number=10, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='verification_status', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.verification_status', index=10, number=11, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='type', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.type', index=11, number=12, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='category', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.category', index=12, number=13, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='criticality', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.criticality', index=13, number=14, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='code', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.code', index=14, number=15, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='patient', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.patient', index=15, number=16, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001\362\377\374\302\006?http://hl7.org/fhir/us/core/StructureDefinition/us-core-patient'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='onset', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.onset', index=16, number=17, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\370\341\343\311\005\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='asserted_date', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.asserted_date', index=17, number=18, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='recorder', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.recorder', index=18, number=19, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Practitioner\362\377\374\302\006/http://hl7.org/fhir/StructureDefinition/Patient'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='asserter', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.asserter', index=19, number=20, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\006/http://hl7.org/fhir/StructureDefinition/Patient\362\377\374\302\0065http://hl7.org/fhir/StructureDefinition/RelatedPerson\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Practitioner'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='last_occurrence', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.last_occurrence', index=20, number=21, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='note', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.note', index=21, number=22, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='reaction', full_name='google.fhir.stu3.uscore.UsCoreAllergyintolerance.reaction', index=22, number=23, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[_USCOREALLERGYINTOLERANCE_ONSET, _USCOREALLERGYINTOLERANCE_REACTION, ], enum_types=[ ], serialized_options=_b('\300\237\343\266\005\003\232\265\216\223\006:http://hl7.org/fhir/StructureDefinition/AllergyIntolerance\262\376\344\227\006Jhttp://hl7.org/fhir/us/core/StructureDefinition/us-core-allergyintolerance'), is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=226, serialized_end=3079, ) _PATIENTUSCOREBIRTHSEXEXTENSION = _descriptor.Descriptor( name='PatientUSCoreBirthSexExtension', full_name='google.fhir.stu3.uscore.PatientUSCoreBirthSexExtension', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.PatientUSCoreBirthSexExtension.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.PatientUSCoreBirthSexExtension.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='value_code', full_name='google.fhir.stu3.uscore.PatientUSCoreBirthSexExtension.value_code', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=_b('\300\237\343\266\005\002\232\265\216\223\0061http://hl7.org/fhir/StructureDefinition/Extension\262\376\344\227\006@http://hl7.org/fhir/us/core/StructureDefinition/us-core-birthsex'), is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=3082, serialized_end=3411, ) _USCORECAREPLAN_ACTIVITY_DETAIL_SCHEDULED = _descriptor.Descriptor( name='Scheduled', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.Detail.Scheduled', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='timing', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.Detail.Scheduled.timing', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='period', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.Detail.Scheduled.period', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='string_value', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.Detail.Scheduled.string_value', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, json_name='string', file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name='scheduled', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.Detail.Scheduled.scheduled', index=0, containing_type=None, fields=[]), ], serialized_start=8914, serialized_end=9102, ) _USCORECAREPLAN_ACTIVITY_DETAIL_PRODUCT = _descriptor.Descriptor( name='Product', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.Detail.Product', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='codeable_concept', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.Detail.Product.codeable_concept', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='reference', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.Detail.Product.reference', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0062http://hl7.org/fhir/StructureDefinition/Medication\362\377\374\302\0061http://hl7.org/fhir/StructureDefinition/Substance'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name='product', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.Detail.Product.product', index=0, containing_type=None, fields=[]), ], serialized_start=9105, serialized_end=9364, ) _USCORECAREPLAN_ACTIVITY_DETAIL = _descriptor.Descriptor( name='Detail', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.Detail', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.Detail.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.Detail.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.Detail.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='category', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.Detail.category', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='definition', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.Detail.definition', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0066http://hl7.org/fhir/StructureDefinition/PlanDefinition\362\377\374\302\006:http://hl7.org/fhir/StructureDefinition/ActivityDefinition\362\377\374\302\0065http://hl7.org/fhir/StructureDefinition/Questionnaire'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='code', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.Detail.code', index=5, number=6, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='reason_code', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.Detail.reason_code', index=6, number=7, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='reason_reference', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.Detail.reason_reference', index=7, number=8, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0061http://hl7.org/fhir/StructureDefinition/Condition'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='goal', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.Detail.goal', index=8, number=9, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\006,http://hl7.org/fhir/StructureDefinition/Goal'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='status', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.Detail.status', index=9, number=10, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='status_reason', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.Detail.status_reason', index=10, number=11, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='prohibited', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.Detail.prohibited', index=11, number=12, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='scheduled', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.Detail.scheduled', index=12, number=13, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\370\341\343\311\005\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='location', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.Detail.location', index=13, number=14, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0060http://hl7.org/fhir/StructureDefinition/Location'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='performer', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.Detail.performer', index=14, number=15, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Practitioner\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Organization\362\377\374\302\0065http://hl7.org/fhir/StructureDefinition/RelatedPerson\362\377\374\302\006/http://hl7.org/fhir/StructureDefinition/Patient\362\377\374\302\0060http://hl7.org/fhir/StructureDefinition/CareTeam'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='product', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.Detail.product', index=15, number=16, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\370\341\343\311\005\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='daily_amount', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.Detail.daily_amount', index=16, number=17, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='quantity', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.Detail.quantity', index=17, number=18, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='description', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.Detail.description', index=18, number=19, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[_USCORECAREPLAN_ACTIVITY_DETAIL_SCHEDULED, _USCORECAREPLAN_ACTIVITY_DETAIL_PRODUCT, ], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=7115, serialized_end=9364, ) _USCORECAREPLAN_ACTIVITY = _descriptor.Descriptor( name='Activity', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='outcome_codeable_concept', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.outcome_codeable_concept', index=3, number=4, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='outcome_reference', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.outcome_reference', index=4, number=5, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0060http://hl7.org/fhir/StructureDefinition/Resource'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='progress', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.progress', index=5, number=6, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='reference', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.reference', index=6, number=7, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0063http://hl7.org/fhir/StructureDefinition/Appointment\362\377\374\302\006<http://hl7.org/fhir/StructureDefinition/CommunicationRequest\362\377\374\302\0065http://hl7.org/fhir/StructureDefinition/DeviceRequest\362\377\374\302\0069http://hl7.org/fhir/StructureDefinition/MedicationRequest\362\377\374\302\0066http://hl7.org/fhir/StructureDefinition/NutritionOrder\362\377\374\302\006,http://hl7.org/fhir/StructureDefinition/Task\362\377\374\302\0068http://hl7.org/fhir/StructureDefinition/ProcedureRequest\362\377\374\302\0067http://hl7.org/fhir/StructureDefinition/ReferralRequest\362\377\374\302\006:http://hl7.org/fhir/StructureDefinition/VisionPrescription\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/RequestGroup'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='detail', full_name='google.fhir.stu3.uscore.UsCoreCareplan.Activity.detail', index=7, number=8, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[_USCORECAREPLAN_ACTIVITY_DETAIL, ], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=5963, serialized_end=9364, ) _USCORECAREPLAN = _descriptor.Descriptor( name='UsCoreCareplan', full_name='google.fhir.stu3.uscore.UsCoreCareplan', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreCareplan.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='meta', full_name='google.fhir.stu3.uscore.UsCoreCareplan.meta', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='implicit_rules', full_name='google.fhir.stu3.uscore.UsCoreCareplan.implicit_rules', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='language', full_name='google.fhir.stu3.uscore.UsCoreCareplan.language', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='text', full_name='google.fhir.stu3.uscore.UsCoreCareplan.text', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='contained', full_name='google.fhir.stu3.uscore.UsCoreCareplan.contained', index=5, number=6, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreCareplan.extension', index=6, number=7, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreCareplan.modifier_extension', index=7, number=8, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='identifier', full_name='google.fhir.stu3.uscore.UsCoreCareplan.identifier', index=8, number=9, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='definition', full_name='google.fhir.stu3.uscore.UsCoreCareplan.definition', index=9, number=10, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0066http://hl7.org/fhir/StructureDefinition/PlanDefinition\362\377\374\302\0065http://hl7.org/fhir/StructureDefinition/Questionnaire'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='based_on', full_name='google.fhir.stu3.uscore.UsCoreCareplan.based_on', index=10, number=11, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0060http://hl7.org/fhir/StructureDefinition/CarePlan'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='replaces', full_name='google.fhir.stu3.uscore.UsCoreCareplan.replaces', index=11, number=12, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0060http://hl7.org/fhir/StructureDefinition/CarePlan'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='part_of', full_name='google.fhir.stu3.uscore.UsCoreCareplan.part_of', index=12, number=13, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0060http://hl7.org/fhir/StructureDefinition/CarePlan'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='status', full_name='google.fhir.stu3.uscore.UsCoreCareplan.status', index=13, number=14, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='intent', full_name='google.fhir.stu3.uscore.UsCoreCareplan.intent', index=14, number=15, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='category', full_name='google.fhir.stu3.uscore.UsCoreCareplan.category', index=15, number=16, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='title', full_name='google.fhir.stu3.uscore.UsCoreCareplan.title', index=16, number=17, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='description', full_name='google.fhir.stu3.uscore.UsCoreCareplan.description', index=17, number=18, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='subject', full_name='google.fhir.stu3.uscore.UsCoreCareplan.subject', index=18, number=19, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001\362\377\374\302\006?http://hl7.org/fhir/us/core/StructureDefinition/us-core-patient'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='context', full_name='google.fhir.stu3.uscore.UsCoreCareplan.context', index=19, number=20, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0061http://hl7.org/fhir/StructureDefinition/Encounter\362\377\374\302\0065http://hl7.org/fhir/StructureDefinition/EpisodeOfCare'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='period', full_name='google.fhir.stu3.uscore.UsCoreCareplan.period', index=20, number=21, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='author', full_name='google.fhir.stu3.uscore.UsCoreCareplan.author', index=21, number=22, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\006/http://hl7.org/fhir/StructureDefinition/Patient\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Practitioner\362\377\374\302\0065http://hl7.org/fhir/StructureDefinition/RelatedPerson\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Organization\362\377\374\302\0060http://hl7.org/fhir/StructureDefinition/CareTeam'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='care_team', full_name='google.fhir.stu3.uscore.UsCoreCareplan.care_team', index=22, number=23, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0060http://hl7.org/fhir/StructureDefinition/CareTeam'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='addresses', full_name='google.fhir.stu3.uscore.UsCoreCareplan.addresses', index=23, number=24, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0061http://hl7.org/fhir/StructureDefinition/Condition'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='supporting_info', full_name='google.fhir.stu3.uscore.UsCoreCareplan.supporting_info', index=24, number=25, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0060http://hl7.org/fhir/StructureDefinition/Resource'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='goal', full_name='google.fhir.stu3.uscore.UsCoreCareplan.goal', index=25, number=26, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\006,http://hl7.org/fhir/StructureDefinition/Goal'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='activity', full_name='google.fhir.stu3.uscore.UsCoreCareplan.activity', index=26, number=27, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='note', full_name='google.fhir.stu3.uscore.UsCoreCareplan.note', index=27, number=28, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[_USCORECAREPLAN_ACTIVITY, ], enum_types=[ ], serialized_options=_b('\300\237\343\266\005\003\232\265\216\223\0060http://hl7.org/fhir/StructureDefinition/CarePlan\262\376\344\227\006@http://hl7.org/fhir/us/core/StructureDefinition/us-core-careplan'), is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=3414, serialized_end=9497, ) _USCORECARETEAM_PARTICIPANT = _descriptor.Descriptor( name='Participant', full_name='google.fhir.stu3.uscore.UsCoreCareteam.Participant', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreCareteam.Participant.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreCareteam.Participant.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreCareteam.Participant.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='role', full_name='google.fhir.stu3.uscore.UsCoreCareteam.Participant.role', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='member', full_name='google.fhir.stu3.uscore.UsCoreCareteam.Participant.member', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001\362\377\374\302\006?http://hl7.org/fhir/us/core/StructureDefinition/us-core-patient\362\377\374\302\006Dhttp://hl7.org/fhir/us/core/StructureDefinition/us-core-practitioner\362\377\374\302\006Dhttp://hl7.org/fhir/us/core/StructureDefinition/us-core-organization\362\377\374\302\0065http://hl7.org/fhir/StructureDefinition/RelatedPerson'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='on_behalf_of', full_name='google.fhir.stu3.uscore.UsCoreCareteam.Participant.on_behalf_of', index=5, number=6, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Organization'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='period', full_name='google.fhir.stu3.uscore.UsCoreCareteam.Participant.period', index=6, number=7, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=10953, serialized_end=11692, ) _USCORECARETEAM = _descriptor.Descriptor( name='UsCoreCareteam', full_name='google.fhir.stu3.uscore.UsCoreCareteam', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreCareteam.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='meta', full_name='google.fhir.stu3.uscore.UsCoreCareteam.meta', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='implicit_rules', full_name='google.fhir.stu3.uscore.UsCoreCareteam.implicit_rules', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='language', full_name='google.fhir.stu3.uscore.UsCoreCareteam.language', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='text', full_name='google.fhir.stu3.uscore.UsCoreCareteam.text', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='contained', full_name='google.fhir.stu3.uscore.UsCoreCareteam.contained', index=5, number=6, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreCareteam.extension', index=6, number=7, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreCareteam.modifier_extension', index=7, number=8, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='identifier', full_name='google.fhir.stu3.uscore.UsCoreCareteam.identifier', index=8, number=9, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='status', full_name='google.fhir.stu3.uscore.UsCoreCareteam.status', index=9, number=10, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='category', full_name='google.fhir.stu3.uscore.UsCoreCareteam.category', index=10, number=11, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='name', full_name='google.fhir.stu3.uscore.UsCoreCareteam.name', index=11, number=12, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='subject', full_name='google.fhir.stu3.uscore.UsCoreCareteam.subject', index=12, number=13, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001\362\377\374\302\006?http://hl7.org/fhir/us/core/StructureDefinition/us-core-patient'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='context', full_name='google.fhir.stu3.uscore.UsCoreCareteam.context', index=13, number=14, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0061http://hl7.org/fhir/StructureDefinition/Encounter\362\377\374\302\0065http://hl7.org/fhir/StructureDefinition/EpisodeOfCare'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='period', full_name='google.fhir.stu3.uscore.UsCoreCareteam.period', index=14, number=15, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='participant', full_name='google.fhir.stu3.uscore.UsCoreCareteam.participant', index=15, number=16, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='reason_code', full_name='google.fhir.stu3.uscore.UsCoreCareteam.reason_code', index=16, number=17, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='reason_reference', full_name='google.fhir.stu3.uscore.UsCoreCareteam.reason_reference', index=17, number=18, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0061http://hl7.org/fhir/StructureDefinition/Condition'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='managing_organization', full_name='google.fhir.stu3.uscore.UsCoreCareteam.managing_organization', index=18, number=19, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Organization'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='note', full_name='google.fhir.stu3.uscore.UsCoreCareteam.note', index=19, number=20, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[_USCORECARETEAM_PARTICIPANT, ], enum_types=[ ], serialized_options=_b('\300\237\343\266\005\003\232\265\216\223\0060http://hl7.org/fhir/StructureDefinition/CareTeam\262\376\344\227\006@http://hl7.org/fhir/us/core/StructureDefinition/us-core-careteam'), is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=9500, serialized_end=11825, ) _USCORECONDITION_ONSET = _descriptor.Descriptor( name='Onset', full_name='google.fhir.stu3.uscore.UsCoreCondition.Onset', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='date_time', full_name='google.fhir.stu3.uscore.UsCoreCondition.Onset.date_time', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='age', full_name='google.fhir.stu3.uscore.UsCoreCondition.Onset.age', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='period', full_name='google.fhir.stu3.uscore.UsCoreCondition.Onset.period', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='range', full_name='google.fhir.stu3.uscore.UsCoreCondition.Onset.range', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='string_value', full_name='google.fhir.stu3.uscore.UsCoreCondition.Onset.string_value', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, json_name='string', file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name='onset', full_name='google.fhir.stu3.uscore.UsCoreCondition.Onset.onset', index=0, containing_type=None, fields=[]), ], serialized_start=2052, serialized_end=2329, ) _USCORECONDITION_ABATEMENT = _descriptor.Descriptor( name='Abatement', full_name='google.fhir.stu3.uscore.UsCoreCondition.Abatement', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='date_time', full_name='google.fhir.stu3.uscore.UsCoreCondition.Abatement.date_time', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='age', full_name='google.fhir.stu3.uscore.UsCoreCondition.Abatement.age', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='boolean', full_name='google.fhir.stu3.uscore.UsCoreCondition.Abatement.boolean', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='period', full_name='google.fhir.stu3.uscore.UsCoreCondition.Abatement.period', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='range', full_name='google.fhir.stu3.uscore.UsCoreCondition.Abatement.range', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='string_value', full_name='google.fhir.stu3.uscore.UsCoreCondition.Abatement.string_value', index=5, number=6, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, json_name='string', file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name='abatement', full_name='google.fhir.stu3.uscore.UsCoreCondition.Abatement.abatement', index=0, containing_type=None, fields=[]), ], serialized_start=13945, serialized_end=14282, ) _USCORECONDITION_STAGE = _descriptor.Descriptor( name='Stage', full_name='google.fhir.stu3.uscore.UsCoreCondition.Stage', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreCondition.Stage.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreCondition.Stage.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreCondition.Stage.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='summary', full_name='google.fhir.stu3.uscore.UsCoreCondition.Stage.summary', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='assessment', full_name='google.fhir.stu3.uscore.UsCoreCondition.Stage.assessment', index=4, number=5, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\006:http://hl7.org/fhir/StructureDefinition/ClinicalImpression\362\377\374\302\0068http://hl7.org/fhir/StructureDefinition/DiagnosticReport\362\377\374\302\0063http://hl7.org/fhir/StructureDefinition/Observation'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=14285, serialized_end=14753, ) _USCORECONDITION_EVIDENCE = _descriptor.Descriptor( name='Evidence', full_name='google.fhir.stu3.uscore.UsCoreCondition.Evidence', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreCondition.Evidence.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreCondition.Evidence.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreCondition.Evidence.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='code', full_name='google.fhir.stu3.uscore.UsCoreCondition.Evidence.code', index=3, number=4, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='detail', full_name='google.fhir.stu3.uscore.UsCoreCondition.Evidence.detail', index=4, number=5, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0060http://hl7.org/fhir/StructureDefinition/Resource'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=14756, serialized_end=15089, ) _USCORECONDITION = _descriptor.Descriptor( name='UsCoreCondition', full_name='google.fhir.stu3.uscore.UsCoreCondition', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreCondition.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='meta', full_name='google.fhir.stu3.uscore.UsCoreCondition.meta', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='implicit_rules', full_name='google.fhir.stu3.uscore.UsCoreCondition.implicit_rules', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='language', full_name='google.fhir.stu3.uscore.UsCoreCondition.language', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='text', full_name='google.fhir.stu3.uscore.UsCoreCondition.text', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='contained', full_name='google.fhir.stu3.uscore.UsCoreCondition.contained', index=5, number=6, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreCondition.extension', index=6, number=7, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreCondition.modifier_extension', index=7, number=8, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='identifier', full_name='google.fhir.stu3.uscore.UsCoreCondition.identifier', index=8, number=9, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='clinical_status', full_name='google.fhir.stu3.uscore.UsCoreCondition.clinical_status', index=9, number=10, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='verification_status', full_name='google.fhir.stu3.uscore.UsCoreCondition.verification_status', index=10, number=11, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='category', full_name='google.fhir.stu3.uscore.UsCoreCondition.category', index=11, number=12, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='severity', full_name='google.fhir.stu3.uscore.UsCoreCondition.severity', index=12, number=13, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='code', full_name='google.fhir.stu3.uscore.UsCoreCondition.code', index=13, number=14, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='body_site', full_name='google.fhir.stu3.uscore.UsCoreCondition.body_site', index=14, number=15, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='subject', full_name='google.fhir.stu3.uscore.UsCoreCondition.subject', index=15, number=16, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001\362\377\374\302\006?http://hl7.org/fhir/us/core/StructureDefinition/us-core-patient'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='context', full_name='google.fhir.stu3.uscore.UsCoreCondition.context', index=16, number=17, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0061http://hl7.org/fhir/StructureDefinition/Encounter\362\377\374\302\0065http://hl7.org/fhir/StructureDefinition/EpisodeOfCare'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='onset', full_name='google.fhir.stu3.uscore.UsCoreCondition.onset', index=17, number=18, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\370\341\343\311\005\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='abatement', full_name='google.fhir.stu3.uscore.UsCoreCondition.abatement', index=18, number=19, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\370\341\343\311\005\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='asserted_date', full_name='google.fhir.stu3.uscore.UsCoreCondition.asserted_date', index=19, number=20, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='asserter', full_name='google.fhir.stu3.uscore.UsCoreCondition.asserter', index=20, number=21, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Practitioner\362\377\374\302\006/http://hl7.org/fhir/StructureDefinition/Patient\362\377\374\302\0065http://hl7.org/fhir/StructureDefinition/RelatedPerson'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='stage', full_name='google.fhir.stu3.uscore.UsCoreCondition.stage', index=21, number=22, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='evidence', full_name='google.fhir.stu3.uscore.UsCoreCondition.evidence', index=22, number=23, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='note', full_name='google.fhir.stu3.uscore.UsCoreCondition.note', index=23, number=24, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[_USCORECONDITION_ONSET, _USCORECONDITION_ABATEMENT, _USCORECONDITION_STAGE, _USCORECONDITION_EVIDENCE, ], enum_types=[ ], serialized_options=_b('\300\237\343\266\005\003\232\265\216\223\0061http://hl7.org/fhir/StructureDefinition/Condition\262\376\344\227\006Ahttp://hl7.org/fhir/us/core/StructureDefinition/us-core-condition'), is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=11828, serialized_end=15224, ) _USCOREDEVICE_UDI = _descriptor.Descriptor( name='Udi', full_name='google.fhir.stu3.uscore.UsCoreDevice.Udi', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreDevice.Udi.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreDevice.Udi.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreDevice.Udi.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='device_identifier', full_name='google.fhir.stu3.uscore.UsCoreDevice.Udi.device_identifier', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='name', full_name='google.fhir.stu3.uscore.UsCoreDevice.Udi.name', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='jurisdiction', full_name='google.fhir.stu3.uscore.UsCoreDevice.Udi.jurisdiction', index=5, number=6, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='carrier_h_r_f', full_name='google.fhir.stu3.uscore.UsCoreDevice.Udi.carrier_h_r_f', index=6, number=7, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='carrier_a_i_d_c', full_name='google.fhir.stu3.uscore.UsCoreDevice.Udi.carrier_a_i_d_c', index=7, number=8, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='issuer', full_name='google.fhir.stu3.uscore.UsCoreDevice.Udi.issuer', index=8, number=9, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='entry_type', full_name='google.fhir.stu3.uscore.UsCoreDevice.Udi.entry_type', index=9, number=10, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=16783, serialized_end=17330, ) _USCOREDEVICE = _descriptor.Descriptor( name='UsCoreDevice', full_name='google.fhir.stu3.uscore.UsCoreDevice', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreDevice.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='meta', full_name='google.fhir.stu3.uscore.UsCoreDevice.meta', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='implicit_rules', full_name='google.fhir.stu3.uscore.UsCoreDevice.implicit_rules', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='language', full_name='google.fhir.stu3.uscore.UsCoreDevice.language', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='text', full_name='google.fhir.stu3.uscore.UsCoreDevice.text', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='contained', full_name='google.fhir.stu3.uscore.UsCoreDevice.contained', index=5, number=6, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreDevice.extension', index=6, number=7, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreDevice.modifier_extension', index=7, number=8, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='identifier', full_name='google.fhir.stu3.uscore.UsCoreDevice.identifier', index=8, number=9, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='udi', full_name='google.fhir.stu3.uscore.UsCoreDevice.udi', index=9, number=10, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='status', full_name='google.fhir.stu3.uscore.UsCoreDevice.status', index=10, number=11, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='type', full_name='google.fhir.stu3.uscore.UsCoreDevice.type', index=11, number=12, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='lot_number', full_name='google.fhir.stu3.uscore.UsCoreDevice.lot_number', index=12, number=13, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='manufacturer', full_name='google.fhir.stu3.uscore.UsCoreDevice.manufacturer', index=13, number=14, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='manufacture_date', full_name='google.fhir.stu3.uscore.UsCoreDevice.manufacture_date', index=14, number=15, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='expiration_date', full_name='google.fhir.stu3.uscore.UsCoreDevice.expiration_date', index=15, number=16, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='model', full_name='google.fhir.stu3.uscore.UsCoreDevice.model', index=16, number=17, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='version', full_name='google.fhir.stu3.uscore.UsCoreDevice.version', index=17, number=18, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='patient', full_name='google.fhir.stu3.uscore.UsCoreDevice.patient', index=18, number=19, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001\362\377\374\302\006?http://hl7.org/fhir/us/core/StructureDefinition/us-core-patient'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='owner', full_name='google.fhir.stu3.uscore.UsCoreDevice.owner', index=19, number=20, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Organization'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='contact', full_name='google.fhir.stu3.uscore.UsCoreDevice.contact', index=20, number=21, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='location', full_name='google.fhir.stu3.uscore.UsCoreDevice.location', index=21, number=22, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0060http://hl7.org/fhir/StructureDefinition/Location'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='url', full_name='google.fhir.stu3.uscore.UsCoreDevice.url', index=22, number=23, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='note', full_name='google.fhir.stu3.uscore.UsCoreDevice.note', index=23, number=24, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='safety', full_name='google.fhir.stu3.uscore.UsCoreDevice.safety', index=24, number=25, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[_USCOREDEVICE_UDI, ], enum_types=[ ], serialized_options=_b('\300\237\343\266\005\003\232\265\216\223\006.http://hl7.org/fhir/StructureDefinition/Device\262\376\344\227\006>http://hl7.org/fhir/us/core/StructureDefinition/us-core-device'), is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=15227, serialized_end=17458, ) _USCOREDIAGNOSTICREPORT_EFFECTIVE = _descriptor.Descriptor( name='Effective', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.Effective', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='date_time', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.Effective.date_time', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='period', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.Effective.period', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name='effective', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.Effective.effective', index=0, containing_type=None, fields=[]), ], serialized_start=19796, serialized_end=19925, ) _USCOREDIAGNOSTICREPORT_PERFORMER = _descriptor.Descriptor( name='Performer', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.Performer', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.Performer.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.Performer.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.Performer.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='role', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.Performer.role', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='actor', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.Performer.actor', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001\362\377\374\302\006Dhttp://hl7.org/fhir/us/core/StructureDefinition/us-core-practitioner\362\377\374\302\006Dhttp://hl7.org/fhir/us/core/StructureDefinition/us-core-organization'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=19928, serialized_end=20363, ) _USCOREDIAGNOSTICREPORT_IMAGE = _descriptor.Descriptor( name='Image', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.Image', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.Image.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.Image.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.Image.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='comment', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.Image.comment', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='link', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.Image.link', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001\362\377\374\302\006-http://hl7.org/fhir/StructureDefinition/Media'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=20366, serialized_end=20691, ) _USCOREDIAGNOSTICREPORT = _descriptor.Descriptor( name='UsCoreDiagnosticreport', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='meta', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.meta', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='implicit_rules', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.implicit_rules', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='language', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.language', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='text', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.text', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='contained', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.contained', index=5, number=6, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.extension', index=6, number=7, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.modifier_extension', index=7, number=8, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='identifier', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.identifier', index=8, number=9, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='based_on', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.based_on', index=9, number=10, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0060http://hl7.org/fhir/StructureDefinition/CarePlan\362\377\374\302\006Bhttp://hl7.org/fhir/StructureDefinition/ImmunizationRecommendation\362\377\374\302\0069http://hl7.org/fhir/StructureDefinition/MedicationRequest\362\377\374\302\0066http://hl7.org/fhir/StructureDefinition/NutritionOrder\362\377\374\302\0068http://hl7.org/fhir/StructureDefinition/ProcedureRequest\362\377\374\302\0067http://hl7.org/fhir/StructureDefinition/ReferralRequest'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='status', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.status', index=10, number=11, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='category', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.category', index=11, number=12, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='code', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.code', index=12, number=13, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='subject', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.subject', index=13, number=14, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001\362\377\374\302\006?http://hl7.org/fhir/us/core/StructureDefinition/us-core-patient'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='context', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.context', index=14, number=15, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0061http://hl7.org/fhir/StructureDefinition/Encounter\362\377\374\302\0065http://hl7.org/fhir/StructureDefinition/EpisodeOfCare'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='effective', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.effective', index=15, number=16, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\370\341\343\311\005\001\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='issued', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.issued', index=16, number=17, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='performer', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.performer', index=17, number=18, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='specimen', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.specimen', index=18, number=19, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0060http://hl7.org/fhir/StructureDefinition/Specimen'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='result', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.result', index=19, number=20, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\006Jhttp://hl7.org/fhir/us/core/StructureDefinition/us-core-observationresults'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='imaging_study', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.imaging_study', index=20, number=21, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/ImagingStudy\362\377\374\302\0067http://hl7.org/fhir/StructureDefinition/ImagingManifest'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='image', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.image', index=21, number=22, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='conclusion', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.conclusion', index=22, number=23, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='coded_diagnosis', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.coded_diagnosis', index=23, number=24, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='presented_form', full_name='google.fhir.stu3.uscore.UsCoreDiagnosticreport.presented_form', index=24, number=25, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[_USCOREDIAGNOSTICREPORT_EFFECTIVE, _USCOREDIAGNOSTICREPORT_PERFORMER, _USCOREDIAGNOSTICREPORT_IMAGE, ], enum_types=[ ], serialized_options=_b('\300\237\343\266\005\003\232\265\216\223\0068http://hl7.org/fhir/StructureDefinition/DiagnosticReport\262\376\344\227\006Hhttp://hl7.org/fhir/us/core/StructureDefinition/us-core-diagnosticreport'), is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=17461, serialized_end=20840, ) _CONTACTPOINTUSCOREDIRECT = _descriptor.Descriptor( name='ContactPointUsCoreDirect', full_name='google.fhir.stu3.uscore.ContactPointUsCoreDirect', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.ContactPointUsCoreDirect.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.ContactPointUsCoreDirect.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='value_boolean', full_name='google.fhir.stu3.uscore.ContactPointUsCoreDirect.value_boolean', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=_b('\300\237\343\266\005\002\232\265\216\223\0061http://hl7.org/fhir/StructureDefinition/Extension\262\376\344\227\006>http://hl7.org/fhir/us/core/StructureDefinition/us-core-direct'), is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=20843, serialized_end=21155, ) _PATIENTUSCOREETHNICITYEXTENSION = _descriptor.Descriptor( name='PatientUSCoreEthnicityExtension', full_name='google.fhir.stu3.uscore.PatientUSCoreEthnicityExtension', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.PatientUSCoreEthnicityExtension.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.PatientUSCoreEthnicityExtension.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='omb_category', full_name='google.fhir.stu3.uscore.PatientUSCoreEthnicityExtension.omb_category', index=2, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='detailed', full_name='google.fhir.stu3.uscore.PatientUSCoreEthnicityExtension.detailed', index=3, number=5, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='text', full_name='google.fhir.stu3.uscore.PatientUSCoreEthnicityExtension.text', index=4, number=6, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=_b('\300\237\343\266\005\002\232\265\216\223\0061http://hl7.org/fhir/StructureDefinition/Extension\262\376\344\227\006Ahttp://hl7.org/fhir/us/core/StructureDefinition/us-core-ethnicity'), is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=21158, serialized_end=21582, ) _USCOREGOAL_START = _descriptor.Descriptor( name='Start', full_name='google.fhir.stu3.uscore.UsCoreGoal.Start', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='date', full_name='google.fhir.stu3.uscore.UsCoreGoal.Start.date', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='codeable_concept', full_name='google.fhir.stu3.uscore.UsCoreGoal.Start.codeable_concept', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name='start', full_name='google.fhir.stu3.uscore.UsCoreGoal.Start.start', index=0, containing_type=None, fields=[]), ], serialized_start=23572, serialized_end=23703, ) _USCOREGOAL_TARGET_DETAIL = _descriptor.Descriptor( name='Detail', full_name='google.fhir.stu3.uscore.UsCoreGoal.Target.Detail', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='quantity', full_name='google.fhir.stu3.uscore.UsCoreGoal.Target.Detail.quantity', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='range', full_name='google.fhir.stu3.uscore.UsCoreGoal.Target.Detail.range', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='codeable_concept', full_name='google.fhir.stu3.uscore.UsCoreGoal.Target.Detail.codeable_concept', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name='detail', full_name='google.fhir.stu3.uscore.UsCoreGoal.Target.Detail.detail', index=0, containing_type=None, fields=[]), ], serialized_start=24080, serialized_end=24269, ) _USCOREGOAL_TARGET_DUE = _descriptor.Descriptor( name='Due', full_name='google.fhir.stu3.uscore.UsCoreGoal.Target.Due', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='date', full_name='google.fhir.stu3.uscore.UsCoreGoal.Target.Due.date', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='duration', full_name='google.fhir.stu3.uscore.UsCoreGoal.Target.Due.duration', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name='due', full_name='google.fhir.stu3.uscore.UsCoreGoal.Target.Due.due', index=0, containing_type=None, fields=[]), ], serialized_start=24271, serialized_end=24383, ) _USCOREGOAL_TARGET = _descriptor.Descriptor( name='Target', full_name='google.fhir.stu3.uscore.UsCoreGoal.Target', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreGoal.Target.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreGoal.Target.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreGoal.Target.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='measure', full_name='google.fhir.stu3.uscore.UsCoreGoal.Target.measure', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='detail', full_name='google.fhir.stu3.uscore.UsCoreGoal.Target.detail', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\370\341\343\311\005\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='due', full_name='google.fhir.stu3.uscore.UsCoreGoal.Target.due', index=5, number=6, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\370\341\343\311\005\001'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[_USCOREGOAL_TARGET_DETAIL, _USCOREGOAL_TARGET_DUE, ], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=23706, serialized_end=24383, ) _USCOREGOAL = _descriptor.Descriptor( name='UsCoreGoal', full_name='google.fhir.stu3.uscore.UsCoreGoal', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreGoal.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='meta', full_name='google.fhir.stu3.uscore.UsCoreGoal.meta', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='implicit_rules', full_name='google.fhir.stu3.uscore.UsCoreGoal.implicit_rules', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='language', full_name='google.fhir.stu3.uscore.UsCoreGoal.language', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='text', full_name='google.fhir.stu3.uscore.UsCoreGoal.text', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='contained', full_name='google.fhir.stu3.uscore.UsCoreGoal.contained', index=5, number=6, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreGoal.extension', index=6, number=7, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreGoal.modifier_extension', index=7, number=8, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='identifier', full_name='google.fhir.stu3.uscore.UsCoreGoal.identifier', index=8, number=9, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='status', full_name='google.fhir.stu3.uscore.UsCoreGoal.status', index=9, number=10, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='category', full_name='google.fhir.stu3.uscore.UsCoreGoal.category', index=10, number=11, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='priority', full_name='google.fhir.stu3.uscore.UsCoreGoal.priority', index=11, number=12, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='description', full_name='google.fhir.stu3.uscore.UsCoreGoal.description', index=12, number=13, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='subject', full_name='google.fhir.stu3.uscore.UsCoreGoal.subject', index=13, number=14, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001\362\377\374\302\006?http://hl7.org/fhir/us/core/StructureDefinition/us-core-patient'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='start', full_name='google.fhir.stu3.uscore.UsCoreGoal.start', index=14, number=15, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\370\341\343\311\005\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='target', full_name='google.fhir.stu3.uscore.UsCoreGoal.target', index=15, number=16, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='status_date', full_name='google.fhir.stu3.uscore.UsCoreGoal.status_date', index=16, number=17, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='status_reason', full_name='google.fhir.stu3.uscore.UsCoreGoal.status_reason', index=17, number=18, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='expressed_by', full_name='google.fhir.stu3.uscore.UsCoreGoal.expressed_by', index=18, number=19, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\006/http://hl7.org/fhir/StructureDefinition/Patient\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Practitioner\362\377\374\302\0065http://hl7.org/fhir/StructureDefinition/RelatedPerson'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='addresses', full_name='google.fhir.stu3.uscore.UsCoreGoal.addresses', index=19, number=20, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0061http://hl7.org/fhir/StructureDefinition/Condition\362\377\374\302\0063http://hl7.org/fhir/StructureDefinition/Observation\362\377\374\302\006;http://hl7.org/fhir/StructureDefinition/MedicationStatement\362\377\374\302\0066http://hl7.org/fhir/StructureDefinition/NutritionOrder\362\377\374\302\0068http://hl7.org/fhir/StructureDefinition/ProcedureRequest\362\377\374\302\0066http://hl7.org/fhir/StructureDefinition/RiskAssessment'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='note', full_name='google.fhir.stu3.uscore.UsCoreGoal.note', index=20, number=21, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='outcome_code', full_name='google.fhir.stu3.uscore.UsCoreGoal.outcome_code', index=21, number=22, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='outcome_reference', full_name='google.fhir.stu3.uscore.UsCoreGoal.outcome_reference', index=22, number=23, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0063http://hl7.org/fhir/StructureDefinition/Observation'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[_USCOREGOAL_START, _USCOREGOAL_TARGET, ], enum_types=[ ], serialized_options=_b('\300\237\343\266\005\003\232\265\216\223\006,http://hl7.org/fhir/StructureDefinition/Goal\262\376\344\227\006<http://hl7.org/fhir/us/core/StructureDefinition/us-core-goal'), is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=21585, serialized_end=24507, ) _USCOREIMMUNIZATION_PRACTITIONER = _descriptor.Descriptor( name='Practitioner', full_name='google.fhir.stu3.uscore.UsCoreImmunization.Practitioner', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreImmunization.Practitioner.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreImmunization.Practitioner.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreImmunization.Practitioner.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='role', full_name='google.fhir.stu3.uscore.UsCoreImmunization.Practitioner.role', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='actor', full_name='google.fhir.stu3.uscore.UsCoreImmunization.Practitioner.actor', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Practitioner'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=26525, serialized_end=26871, ) _USCOREIMMUNIZATION_EXPLANATION = _descriptor.Descriptor( name='Explanation', full_name='google.fhir.stu3.uscore.UsCoreImmunization.Explanation', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreImmunization.Explanation.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreImmunization.Explanation.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreImmunization.Explanation.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='reason', full_name='google.fhir.stu3.uscore.UsCoreImmunization.Explanation.reason', index=3, number=4, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='reason_not_given', full_name='google.fhir.stu3.uscore.UsCoreImmunization.Explanation.reason_not_given', index=4, number=5, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=26874, serialized_end=27172, ) _USCOREIMMUNIZATION_REACTION = _descriptor.Descriptor( name='Reaction', full_name='google.fhir.stu3.uscore.UsCoreImmunization.Reaction', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreImmunization.Reaction.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreImmunization.Reaction.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreImmunization.Reaction.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='date', full_name='google.fhir.stu3.uscore.UsCoreImmunization.Reaction.date', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='detail', full_name='google.fhir.stu3.uscore.UsCoreImmunization.Reaction.detail', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0063http://hl7.org/fhir/StructureDefinition/Observation'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='reported', full_name='google.fhir.stu3.uscore.UsCoreImmunization.Reaction.reported', index=5, number=6, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=27175, serialized_end=27555, ) _USCOREIMMUNIZATION_VACCINATIONPROTOCOL = _descriptor.Descriptor( name='VaccinationProtocol', full_name='google.fhir.stu3.uscore.UsCoreImmunization.VaccinationProtocol', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreImmunization.VaccinationProtocol.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreImmunization.VaccinationProtocol.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreImmunization.VaccinationProtocol.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='dose_sequence', full_name='google.fhir.stu3.uscore.UsCoreImmunization.VaccinationProtocol.dose_sequence', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='description', full_name='google.fhir.stu3.uscore.UsCoreImmunization.VaccinationProtocol.description', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='authority', full_name='google.fhir.stu3.uscore.UsCoreImmunization.VaccinationProtocol.authority', index=5, number=6, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Organization'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='series', full_name='google.fhir.stu3.uscore.UsCoreImmunization.VaccinationProtocol.series', index=6, number=7, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='series_doses', full_name='google.fhir.stu3.uscore.UsCoreImmunization.VaccinationProtocol.series_doses', index=7, number=8, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='target_disease', full_name='google.fhir.stu3.uscore.UsCoreImmunization.VaccinationProtocol.target_disease', index=8, number=9, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='dose_status', full_name='google.fhir.stu3.uscore.UsCoreImmunization.VaccinationProtocol.dose_status', index=9, number=10, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='dose_status_reason', full_name='google.fhir.stu3.uscore.UsCoreImmunization.VaccinationProtocol.dose_status_reason', index=10, number=11, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=27558, serialized_end=28286, ) _USCOREIMMUNIZATION = _descriptor.Descriptor( name='UsCoreImmunization', full_name='google.fhir.stu3.uscore.UsCoreImmunization', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreImmunization.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='meta', full_name='google.fhir.stu3.uscore.UsCoreImmunization.meta', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='implicit_rules', full_name='google.fhir.stu3.uscore.UsCoreImmunization.implicit_rules', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='language', full_name='google.fhir.stu3.uscore.UsCoreImmunization.language', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='text', full_name='google.fhir.stu3.uscore.UsCoreImmunization.text', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='contained', full_name='google.fhir.stu3.uscore.UsCoreImmunization.contained', index=5, number=6, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreImmunization.extension', index=6, number=7, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreImmunization.modifier_extension', index=7, number=8, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='identifier', full_name='google.fhir.stu3.uscore.UsCoreImmunization.identifier', index=8, number=9, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='status', full_name='google.fhir.stu3.uscore.UsCoreImmunization.status', index=9, number=10, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='not_given', full_name='google.fhir.stu3.uscore.UsCoreImmunization.not_given', index=10, number=11, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='vaccine_code', full_name='google.fhir.stu3.uscore.UsCoreImmunization.vaccine_code', index=11, number=12, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='patient', full_name='google.fhir.stu3.uscore.UsCoreImmunization.patient', index=12, number=13, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001\362\377\374\302\006?http://hl7.org/fhir/us/core/StructureDefinition/us-core-patient'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='encounter', full_name='google.fhir.stu3.uscore.UsCoreImmunization.encounter', index=13, number=14, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0061http://hl7.org/fhir/StructureDefinition/Encounter'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='date', full_name='google.fhir.stu3.uscore.UsCoreImmunization.date', index=14, number=15, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='primary_source', full_name='google.fhir.stu3.uscore.UsCoreImmunization.primary_source', index=15, number=16, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='report_origin', full_name='google.fhir.stu3.uscore.UsCoreImmunization.report_origin', index=16, number=17, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='location', full_name='google.fhir.stu3.uscore.UsCoreImmunization.location', index=17, number=18, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0060http://hl7.org/fhir/StructureDefinition/Location'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='manufacturer', full_name='google.fhir.stu3.uscore.UsCoreImmunization.manufacturer', index=18, number=19, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Organization'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='lot_number', full_name='google.fhir.stu3.uscore.UsCoreImmunization.lot_number', index=19, number=20, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='expiration_date', full_name='google.fhir.stu3.uscore.UsCoreImmunization.expiration_date', index=20, number=21, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='site', full_name='google.fhir.stu3.uscore.UsCoreImmunization.site', index=21, number=22, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='route', full_name='google.fhir.stu3.uscore.UsCoreImmunization.route', index=22, number=23, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='dose_quantity', full_name='google.fhir.stu3.uscore.UsCoreImmunization.dose_quantity', index=23, number=24, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='practitioner', full_name='google.fhir.stu3.uscore.UsCoreImmunization.practitioner', index=24, number=25, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='note', full_name='google.fhir.stu3.uscore.UsCoreImmunization.note', index=25, number=26, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='explanation', full_name='google.fhir.stu3.uscore.UsCoreImmunization.explanation', index=26, number=27, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='reaction', full_name='google.fhir.stu3.uscore.UsCoreImmunization.reaction', index=27, number=28, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='vaccination_protocol', full_name='google.fhir.stu3.uscore.UsCoreImmunization.vaccination_protocol', index=28, number=29, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[_USCOREIMMUNIZATION_PRACTITIONER, _USCOREIMMUNIZATION_EXPLANATION, _USCOREIMMUNIZATION_REACTION, _USCOREIMMUNIZATION_VACCINATIONPROTOCOL, ], enum_types=[ ], serialized_options=_b('\300\237\343\266\005\003\232\265\216\223\0064http://hl7.org/fhir/StructureDefinition/Immunization\262\376\344\227\006Dhttp://hl7.org/fhir/us/core/StructureDefinition/us-core-immunization'), is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=24510, serialized_end=28427, ) _USCORELOCATION_POSITION = _descriptor.Descriptor( name='Position', full_name='google.fhir.stu3.uscore.UsCoreLocation.Position', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreLocation.Position.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreLocation.Position.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreLocation.Position.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='longitude', full_name='google.fhir.stu3.uscore.UsCoreLocation.Position.longitude', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='latitude', full_name='google.fhir.stu3.uscore.UsCoreLocation.Position.latitude', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='altitude', full_name='google.fhir.stu3.uscore.UsCoreLocation.Position.altitude', index=5, number=6, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=29908, serialized_end=30249, ) _USCORELOCATION = _descriptor.Descriptor( name='UsCoreLocation', full_name='google.fhir.stu3.uscore.UsCoreLocation', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreLocation.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='meta', full_name='google.fhir.stu3.uscore.UsCoreLocation.meta', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='implicit_rules', full_name='google.fhir.stu3.uscore.UsCoreLocation.implicit_rules', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='language', full_name='google.fhir.stu3.uscore.UsCoreLocation.language', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='text', full_name='google.fhir.stu3.uscore.UsCoreLocation.text', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='contained', full_name='google.fhir.stu3.uscore.UsCoreLocation.contained', index=5, number=6, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreLocation.extension', index=6, number=7, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreLocation.modifier_extension', index=7, number=8, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='identifier', full_name='google.fhir.stu3.uscore.UsCoreLocation.identifier', index=8, number=9, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='status', full_name='google.fhir.stu3.uscore.UsCoreLocation.status', index=9, number=10, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='operational_status', full_name='google.fhir.stu3.uscore.UsCoreLocation.operational_status', index=10, number=11, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='name', full_name='google.fhir.stu3.uscore.UsCoreLocation.name', index=11, number=12, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='alias', full_name='google.fhir.stu3.uscore.UsCoreLocation.alias', index=12, number=13, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='description', full_name='google.fhir.stu3.uscore.UsCoreLocation.description', index=13, number=14, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='mode', full_name='google.fhir.stu3.uscore.UsCoreLocation.mode', index=14, number=15, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='type', full_name='google.fhir.stu3.uscore.UsCoreLocation.type', index=15, number=16, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='telecom', full_name='google.fhir.stu3.uscore.UsCoreLocation.telecom', index=16, number=17, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='address', full_name='google.fhir.stu3.uscore.UsCoreLocation.address', index=17, number=18, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='physical_type', full_name='google.fhir.stu3.uscore.UsCoreLocation.physical_type', index=18, number=19, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='position', full_name='google.fhir.stu3.uscore.UsCoreLocation.position', index=19, number=20, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='managing_organization', full_name='google.fhir.stu3.uscore.UsCoreLocation.managing_organization', index=20, number=21, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\006Dhttp://hl7.org/fhir/us/core/StructureDefinition/us-core-organization'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='part_of', full_name='google.fhir.stu3.uscore.UsCoreLocation.part_of', index=21, number=22, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0060http://hl7.org/fhir/StructureDefinition/Location'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='endpoint', full_name='google.fhir.stu3.uscore.UsCoreLocation.endpoint', index=22, number=23, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0060http://hl7.org/fhir/StructureDefinition/Endpoint'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[_USCORELOCATION_POSITION, ], enum_types=[ ], serialized_options=_b('\300\237\343\266\005\003\232\265\216\223\0060http://hl7.org/fhir/StructureDefinition/Location\262\376\344\227\006@http://hl7.org/fhir/us/core/StructureDefinition/us-core-location'), is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=28430, serialized_end=30382, ) _USCOREMEDICATION_INGREDIENT_ITEM = _descriptor.Descriptor( name='Item', full_name='google.fhir.stu3.uscore.UsCoreMedication.Ingredient.Item', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='codeable_concept', full_name='google.fhir.stu3.uscore.UsCoreMedication.Ingredient.Item.codeable_concept', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='reference', full_name='google.fhir.stu3.uscore.UsCoreMedication.Ingredient.Item.reference', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0061http://hl7.org/fhir/StructureDefinition/Substance\362\377\374\302\0062http://hl7.org/fhir/StructureDefinition/Medication'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name='item', full_name='google.fhir.stu3.uscore.UsCoreMedication.Ingredient.Item.item', index=0, containing_type=None, fields=[]), ], serialized_start=31807, serialized_end=32060, ) _USCOREMEDICATION_INGREDIENT = _descriptor.Descriptor( name='Ingredient', full_name='google.fhir.stu3.uscore.UsCoreMedication.Ingredient', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreMedication.Ingredient.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreMedication.Ingredient.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreMedication.Ingredient.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='item', full_name='google.fhir.stu3.uscore.UsCoreMedication.Ingredient.item', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\370\341\343\311\005\001\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='is_active', full_name='google.fhir.stu3.uscore.UsCoreMedication.Ingredient.is_active', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='amount', full_name='google.fhir.stu3.uscore.UsCoreMedication.Ingredient.amount', index=5, number=6, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[_USCOREMEDICATION_INGREDIENT_ITEM, ], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=31445, serialized_end=32060, ) _USCOREMEDICATION_PACKAGE_CONTENT_ITEM = _descriptor.Descriptor( name='Item', full_name='google.fhir.stu3.uscore.UsCoreMedication.Package.Content.Item', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='codeable_concept', full_name='google.fhir.stu3.uscore.UsCoreMedication.Package.Content.Item.codeable_concept', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='reference', full_name='google.fhir.stu3.uscore.UsCoreMedication.Package.Content.Item.reference', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0062http://hl7.org/fhir/StructureDefinition/Medication'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name='item', full_name='google.fhir.stu3.uscore.UsCoreMedication.Package.Content.Item.item', index=0, containing_type=None, fields=[]), ], serialized_start=32765, serialized_end=32962, ) _USCOREMEDICATION_PACKAGE_CONTENT = _descriptor.Descriptor( name='Content', full_name='google.fhir.stu3.uscore.UsCoreMedication.Package.Content', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreMedication.Package.Content.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreMedication.Package.Content.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreMedication.Package.Content.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='item', full_name='google.fhir.stu3.uscore.UsCoreMedication.Package.Content.item', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\370\341\343\311\005\001\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='amount', full_name='google.fhir.stu3.uscore.UsCoreMedication.Package.Content.amount', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[_USCOREMEDICATION_PACKAGE_CONTENT_ITEM, ], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=32444, serialized_end=32962, ) _USCOREMEDICATION_PACKAGE_BATCH = _descriptor.Descriptor( name='Batch', full_name='google.fhir.stu3.uscore.UsCoreMedication.Package.Batch', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreMedication.Package.Batch.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreMedication.Package.Batch.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreMedication.Package.Batch.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='lot_number', full_name='google.fhir.stu3.uscore.UsCoreMedication.Package.Batch.lot_number', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='expiration_date', full_name='google.fhir.stu3.uscore.UsCoreMedication.Package.Batch.expiration_date', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=32965, serialized_end=33244, ) _USCOREMEDICATION_PACKAGE = _descriptor.Descriptor( name='Package', full_name='google.fhir.stu3.uscore.UsCoreMedication.Package', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreMedication.Package.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreMedication.Package.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreMedication.Package.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='container', full_name='google.fhir.stu3.uscore.UsCoreMedication.Package.container', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='content', full_name='google.fhir.stu3.uscore.UsCoreMedication.Package.content', index=4, number=5, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='batch', full_name='google.fhir.stu3.uscore.UsCoreMedication.Package.batch', index=5, number=6, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[_USCOREMEDICATION_PACKAGE_CONTENT, _USCOREMEDICATION_PACKAGE_BATCH, ], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=32063, serialized_end=33244, ) _USCOREMEDICATION = _descriptor.Descriptor( name='UsCoreMedication', full_name='google.fhir.stu3.uscore.UsCoreMedication', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreMedication.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='meta', full_name='google.fhir.stu3.uscore.UsCoreMedication.meta', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='implicit_rules', full_name='google.fhir.stu3.uscore.UsCoreMedication.implicit_rules', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='language', full_name='google.fhir.stu3.uscore.UsCoreMedication.language', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='text', full_name='google.fhir.stu3.uscore.UsCoreMedication.text', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='contained', full_name='google.fhir.stu3.uscore.UsCoreMedication.contained', index=5, number=6, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreMedication.extension', index=6, number=7, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreMedication.modifier_extension', index=7, number=8, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='code', full_name='google.fhir.stu3.uscore.UsCoreMedication.code', index=8, number=9, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='status', full_name='google.fhir.stu3.uscore.UsCoreMedication.status', index=9, number=10, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='is_brand', full_name='google.fhir.stu3.uscore.UsCoreMedication.is_brand', index=10, number=11, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='is_over_the_counter', full_name='google.fhir.stu3.uscore.UsCoreMedication.is_over_the_counter', index=11, number=12, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='manufacturer', full_name='google.fhir.stu3.uscore.UsCoreMedication.manufacturer', index=12, number=13, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Organization'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='form', full_name='google.fhir.stu3.uscore.UsCoreMedication.form', index=13, number=14, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='ingredient', full_name='google.fhir.stu3.uscore.UsCoreMedication.ingredient', index=14, number=15, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='package_value', full_name='google.fhir.stu3.uscore.UsCoreMedication.package_value', index=15, number=16, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, json_name='package', file=DESCRIPTOR), _descriptor.FieldDescriptor( name='image', full_name='google.fhir.stu3.uscore.UsCoreMedication.image', index=16, number=17, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[_USCOREMEDICATION_INGREDIENT, _USCOREMEDICATION_PACKAGE, ], enum_types=[ ], serialized_options=_b('\300\237\343\266\005\003\232\265\216\223\0062http://hl7.org/fhir/StructureDefinition/Medication\262\376\344\227\006Bhttp://hl7.org/fhir/us/core/StructureDefinition/us-core-medication'), is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=30385, serialized_end=33381, ) _USCOREMEDICATIONREQUEST_MEDICATION = _descriptor.Descriptor( name='Medication', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.Medication', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='codeable_concept', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.Medication.codeable_concept', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='reference', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.Medication.reference', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0062http://hl7.org/fhir/StructureDefinition/Medication'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name='medication', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.Medication.medication', index=0, containing_type=None, fields=[]), ], serialized_start=36384, serialized_end=36593, ) _USCOREMEDICATIONREQUEST_REQUESTER = _descriptor.Descriptor( name='Requester', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.Requester', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.Requester.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.Requester.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.Requester.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='agent', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.Requester.agent', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001\362\377\374\302\006Dhttp://hl7.org/fhir/us/core/StructureDefinition/us-core-practitioner'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='on_behalf_of', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.Requester.on_behalf_of', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Organization'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=36596, serialized_end=37018, ) _USCOREMEDICATIONREQUEST_DISPENSEREQUEST = _descriptor.Descriptor( name='DispenseRequest', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.DispenseRequest', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.DispenseRequest.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.DispenseRequest.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.DispenseRequest.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='validity_period', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.DispenseRequest.validity_period', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='number_of_repeats_allowed', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.DispenseRequest.number_of_repeats_allowed', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='quantity', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.DispenseRequest.quantity', index=5, number=6, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='expected_supply_duration', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.DispenseRequest.expected_supply_duration', index=6, number=7, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='performer', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.DispenseRequest.performer', index=7, number=8, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Organization'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=37021, serialized_end=37568, ) _USCOREMEDICATIONREQUEST_SUBSTITUTION = _descriptor.Descriptor( name='Substitution', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.Substitution', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.Substitution.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.Substitution.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.Substitution.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='allowed', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.Substitution.allowed', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='reason', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.Substitution.reason', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=37571, serialized_end=37861, ) _USCOREMEDICATIONREQUEST = _descriptor.Descriptor( name='UsCoreMedicationrequest', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='meta', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.meta', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='implicit_rules', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.implicit_rules', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='language', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.language', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='text', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.text', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='contained', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.contained', index=5, number=6, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.extension', index=6, number=7, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.modifier_extension', index=7, number=8, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='identifier', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.identifier', index=8, number=9, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='definition', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.definition', index=9, number=10, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\006:http://hl7.org/fhir/StructureDefinition/ActivityDefinition\362\377\374\302\0066http://hl7.org/fhir/StructureDefinition/PlanDefinition'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='based_on', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.based_on', index=10, number=11, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0060http://hl7.org/fhir/StructureDefinition/CarePlan\362\377\374\302\0069http://hl7.org/fhir/StructureDefinition/MedicationRequest\362\377\374\302\0068http://hl7.org/fhir/StructureDefinition/ProcedureRequest\362\377\374\302\0067http://hl7.org/fhir/StructureDefinition/ReferralRequest'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='group_identifier', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.group_identifier', index=11, number=12, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='status', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.status', index=12, number=13, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='intent', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.intent', index=13, number=14, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='category', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.category', index=14, number=15, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='priority', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.priority', index=15, number=16, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='medication', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.medication', index=16, number=17, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\370\341\343\311\005\001\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='subject', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.subject', index=17, number=18, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001\362\377\374\302\006?http://hl7.org/fhir/us/core/StructureDefinition/us-core-patient'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='context', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.context', index=18, number=19, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0061http://hl7.org/fhir/StructureDefinition/Encounter\362\377\374\302\0065http://hl7.org/fhir/StructureDefinition/EpisodeOfCare'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='supporting_information', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.supporting_information', index=19, number=20, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0060http://hl7.org/fhir/StructureDefinition/Resource'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='authored_on', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.authored_on', index=20, number=21, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='requester', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.requester', index=21, number=22, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='recorder', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.recorder', index=22, number=23, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Practitioner'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='reason_code', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.reason_code', index=23, number=24, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='reason_reference', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.reason_reference', index=24, number=25, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0061http://hl7.org/fhir/StructureDefinition/Condition\362\377\374\302\0063http://hl7.org/fhir/StructureDefinition/Observation'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='note', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.note', index=25, number=26, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='dosage_instruction', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.dosage_instruction', index=26, number=27, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='dispense_request', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.dispense_request', index=27, number=28, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='substitution', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.substitution', index=28, number=29, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='prior_prescription', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.prior_prescription', index=29, number=30, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0069http://hl7.org/fhir/StructureDefinition/MedicationRequest'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='detected_issue', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.detected_issue', index=30, number=31, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0065http://hl7.org/fhir/StructureDefinition/DetectedIssue'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='event_history', full_name='google.fhir.stu3.uscore.UsCoreMedicationrequest.event_history', index=31, number=32, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0062http://hl7.org/fhir/StructureDefinition/Provenance'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[_USCOREMEDICATIONREQUEST_MEDICATION, _USCOREMEDICATIONREQUEST_REQUESTER, _USCOREMEDICATIONREQUEST_DISPENSEREQUEST, _USCOREMEDICATIONREQUEST_SUBSTITUTION, ], enum_types=[ ], serialized_options=_b('\300\237\343\266\005\003\232\265\216\223\0069http://hl7.org/fhir/StructureDefinition/MedicationRequest\262\376\344\227\006Ihttp://hl7.org/fhir/us/core/StructureDefinition/us-core-medicationrequest'), is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=33384, serialized_end=38012, ) _USCOREMEDICATIONSTATEMENT_MEDICATION = _descriptor.Descriptor( name='Medication', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.Medication', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='codeable_concept', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.Medication.codeable_concept', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='reference', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.Medication.reference', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0062http://hl7.org/fhir/StructureDefinition/Medication'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name='medication', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.Medication.medication', index=0, containing_type=None, fields=[]), ], serialized_start=36384, serialized_end=36593, ) _USCOREMEDICATIONSTATEMENT_EFFECTIVE = _descriptor.Descriptor( name='Effective', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.Effective', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='date_time', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.Effective.date_time', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='period', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.Effective.period', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name='effective', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.Effective.effective', index=0, containing_type=None, fields=[]), ], serialized_start=19796, serialized_end=19925, ) _USCOREMEDICATIONSTATEMENT = _descriptor.Descriptor( name='UsCoreMedicationstatement', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='meta', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.meta', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='implicit_rules', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.implicit_rules', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='language', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.language', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='text', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.text', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='contained', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.contained', index=5, number=6, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.extension', index=6, number=7, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.modifier_extension', index=7, number=8, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='identifier', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.identifier', index=8, number=9, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='based_on', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.based_on', index=9, number=10, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0069http://hl7.org/fhir/StructureDefinition/MedicationRequest\362\377\374\302\0060http://hl7.org/fhir/StructureDefinition/CarePlan\362\377\374\302\0068http://hl7.org/fhir/StructureDefinition/ProcedureRequest\362\377\374\302\0067http://hl7.org/fhir/StructureDefinition/ReferralRequest'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='part_of', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.part_of', index=10, number=11, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\006@http://hl7.org/fhir/StructureDefinition/MedicationAdministration\362\377\374\302\006:http://hl7.org/fhir/StructureDefinition/MedicationDispense\362\377\374\302\006;http://hl7.org/fhir/StructureDefinition/MedicationStatement\362\377\374\302\0061http://hl7.org/fhir/StructureDefinition/Procedure\362\377\374\302\0063http://hl7.org/fhir/StructureDefinition/Observation'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='context', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.context', index=11, number=12, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0061http://hl7.org/fhir/StructureDefinition/Encounter\362\377\374\302\0065http://hl7.org/fhir/StructureDefinition/EpisodeOfCare'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='status', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.status', index=12, number=13, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='category', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.category', index=13, number=14, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='medication', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.medication', index=14, number=15, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\370\341\343\311\005\001\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='effective', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.effective', index=15, number=16, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\370\341\343\311\005\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='date_asserted', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.date_asserted', index=16, number=17, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='information_source', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.information_source', index=17, number=18, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\006/http://hl7.org/fhir/StructureDefinition/Patient\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Practitioner\362\377\374\302\0065http://hl7.org/fhir/StructureDefinition/RelatedPerson\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Organization'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='subject', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.subject', index=18, number=19, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001\362\377\374\302\006?http://hl7.org/fhir/us/core/StructureDefinition/us-core-patient'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='derived_from', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.derived_from', index=19, number=20, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0060http://hl7.org/fhir/StructureDefinition/Resource'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='taken', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.taken', index=20, number=21, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='reason_not_taken', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.reason_not_taken', index=21, number=22, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='reason_code', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.reason_code', index=22, number=23, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='reason_reference', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.reason_reference', index=23, number=24, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0061http://hl7.org/fhir/StructureDefinition/Condition\362\377\374\302\0063http://hl7.org/fhir/StructureDefinition/Observation'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='note', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.note', index=24, number=25, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='dosage', full_name='google.fhir.stu3.uscore.UsCoreMedicationstatement.dosage', index=25, number=26, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[_USCOREMEDICATIONSTATEMENT_MEDICATION, _USCOREMEDICATIONSTATEMENT_EFFECTIVE, ], enum_types=[ ], serialized_options=_b('\300\237\343\266\005\003\232\265\216\223\006;http://hl7.org/fhir/StructureDefinition/MedicationStatement\262\376\344\227\006Khttp://hl7.org/fhir/us/core/StructureDefinition/us-core-medicationstatement'), is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=38015, serialized_end=41257, ) _USCOREOBSERVATIONRESULTS_EFFECTIVE = _descriptor.Descriptor( name='Effective', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Effective', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='date_time', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Effective.date_time', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='period', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Effective.period', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name='effective', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Effective.effective', index=0, containing_type=None, fields=[]), ], serialized_start=19796, serialized_end=19925, ) _USCOREOBSERVATIONRESULTS_VALUE = _descriptor.Descriptor( name='Value', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Value', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='quantity', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Value.quantity', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='codeable_concept', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Value.codeable_concept', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='string_value', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Value.string_value', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, json_name='string', file=DESCRIPTOR), _descriptor.FieldDescriptor( name='boolean', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Value.boolean', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='range', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Value.range', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='ratio', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Value.ratio', index=5, number=6, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='sampled_data', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Value.sampled_data', index=6, number=7, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='attachment', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Value.attachment', index=7, number=8, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='time', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Value.time', index=8, number=9, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='date_time', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Value.date_time', index=9, number=10, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='period', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Value.period', index=10, number=11, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name='value', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Value.value', index=0, containing_type=None, fields=[]), ], serialized_start=44208, serialized_end=44829, ) _USCOREOBSERVATIONRESULTS_REFERENCERANGE = _descriptor.Descriptor( name='ReferenceRange', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.ReferenceRange', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.ReferenceRange.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.ReferenceRange.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.ReferenceRange.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='low', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.ReferenceRange.low', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='high', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.ReferenceRange.high', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='type', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.ReferenceRange.type', index=5, number=6, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='applies_to', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.ReferenceRange.applies_to', index=6, number=7, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='age', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.ReferenceRange.age', index=7, number=8, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='text', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.ReferenceRange.text', index=8, number=9, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=44832, serialized_end=45322, ) _USCOREOBSERVATIONRESULTS_RELATED = _descriptor.Descriptor( name='Related', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Related', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Related.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Related.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Related.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='type', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Related.type', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='target', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Related.target', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001\362\377\374\302\0063http://hl7.org/fhir/StructureDefinition/Observation\362\377\374\302\006=http://hl7.org/fhir/StructureDefinition/QuestionnaireResponse\362\377\374\302\0060http://hl7.org/fhir/StructureDefinition/Sequence'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=45325, serialized_end=45805, ) _USCOREOBSERVATIONRESULTS_COMPONENT_VALUE = _descriptor.Descriptor( name='Value', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Component.Value', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='quantity', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Component.Value.quantity', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='codeable_concept', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Component.Value.codeable_concept', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='string_value', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Component.Value.string_value', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, json_name='string', file=DESCRIPTOR), _descriptor.FieldDescriptor( name='range', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Component.Value.range', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='ratio', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Component.Value.ratio', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='sampled_data', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Component.Value.sampled_data', index=5, number=6, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='attachment', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Component.Value.attachment', index=6, number=7, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='time', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Component.Value.time', index=7, number=8, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='date_time', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Component.Value.date_time', index=8, number=9, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='period', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Component.Value.period', index=9, number=10, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name='value', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Component.Value.value', index=0, containing_type=None, fields=[]), ], serialized_start=46361, serialized_end=46930, ) _USCOREOBSERVATIONRESULTS_COMPONENT = _descriptor.Descriptor( name='Component', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Component', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Component.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Component.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Component.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='code', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Component.code', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='value', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Component.value', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\370\341\343\311\005\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='data_absent_reason', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Component.data_absent_reason', index=5, number=6, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='interpretation', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Component.interpretation', index=6, number=7, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='reference_range', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.Component.reference_range', index=7, number=8, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[_USCOREOBSERVATIONRESULTS_COMPONENT_VALUE, ], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=45808, serialized_end=46930, ) _USCOREOBSERVATIONRESULTS = _descriptor.Descriptor( name='UsCoreObservationresults', full_name='google.fhir.stu3.uscore.UsCoreObservationresults', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='meta', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.meta', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='implicit_rules', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.implicit_rules', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='language', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.language', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='text', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.text', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='contained', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.contained', index=5, number=6, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.extension', index=6, number=7, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.modifier_extension', index=7, number=8, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='identifier', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.identifier', index=8, number=9, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='based_on', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.based_on', index=9, number=10, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0060http://hl7.org/fhir/StructureDefinition/CarePlan\362\377\374\302\0065http://hl7.org/fhir/StructureDefinition/DeviceRequest\362\377\374\302\006Bhttp://hl7.org/fhir/StructureDefinition/ImmunizationRecommendation\362\377\374\302\0069http://hl7.org/fhir/StructureDefinition/MedicationRequest\362\377\374\302\0066http://hl7.org/fhir/StructureDefinition/NutritionOrder\362\377\374\302\0068http://hl7.org/fhir/StructureDefinition/ProcedureRequest\362\377\374\302\0067http://hl7.org/fhir/StructureDefinition/ReferralRequest'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='status', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.status', index=10, number=11, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='category', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.category', index=11, number=12, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='code', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.code', index=12, number=13, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='subject', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.subject', index=13, number=14, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001\362\377\374\302\006?http://hl7.org/fhir/us/core/StructureDefinition/us-core-patient'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='context', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.context', index=14, number=15, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0061http://hl7.org/fhir/StructureDefinition/Encounter\362\377\374\302\0065http://hl7.org/fhir/StructureDefinition/EpisodeOfCare'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='effective', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.effective', index=15, number=16, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\370\341\343\311\005\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='issued', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.issued', index=16, number=17, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='performer', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.performer', index=17, number=18, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Practitioner\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Organization\362\377\374\302\006/http://hl7.org/fhir/StructureDefinition/Patient\362\377\374\302\0065http://hl7.org/fhir/StructureDefinition/RelatedPerson'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='value', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.value', index=18, number=19, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\370\341\343\311\005\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='data_absent_reason', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.data_absent_reason', index=19, number=20, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='interpretation', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.interpretation', index=20, number=21, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='comment', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.comment', index=21, number=22, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='body_site', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.body_site', index=22, number=23, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='method', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.method', index=23, number=24, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='specimen', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.specimen', index=24, number=25, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0060http://hl7.org/fhir/StructureDefinition/Specimen'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='device', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.device', index=25, number=26, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\006.http://hl7.org/fhir/StructureDefinition/Device\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/DeviceMetric'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='reference_range', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.reference_range', index=26, number=27, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='related', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.related', index=27, number=28, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='component', full_name='google.fhir.stu3.uscore.UsCoreObservationresults.component', index=28, number=29, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[_USCOREOBSERVATIONRESULTS_EFFECTIVE, _USCOREOBSERVATIONRESULTS_VALUE, _USCOREOBSERVATIONRESULTS_REFERENCERANGE, _USCOREOBSERVATIONRESULTS_RELATED, _USCOREOBSERVATIONRESULTS_COMPONENT, ], enum_types=[ ], serialized_options=_b('\300\237\343\266\005\003\232\265\216\223\0063http://hl7.org/fhir/StructureDefinition/Observation\262\376\344\227\006Jhttp://hl7.org/fhir/us/core/StructureDefinition/us-core-observationresults'), is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=41260, serialized_end=47076, ) _USCOREORGANIZATION_CONTACT = _descriptor.Descriptor( name='Contact', full_name='google.fhir.stu3.uscore.UsCoreOrganization.Contact', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreOrganization.Contact.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreOrganization.Contact.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreOrganization.Contact.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='purpose', full_name='google.fhir.stu3.uscore.UsCoreOrganization.Contact.purpose', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='name', full_name='google.fhir.stu3.uscore.UsCoreOrganization.Contact.name', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='telecom', full_name='google.fhir.stu3.uscore.UsCoreOrganization.Contact.telecom', index=5, number=6, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='address', full_name='google.fhir.stu3.uscore.UsCoreOrganization.Contact.address', index=6, number=7, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=48212, serialized_end=48594, ) _USCOREORGANIZATION = _descriptor.Descriptor( name='UsCoreOrganization', full_name='google.fhir.stu3.uscore.UsCoreOrganization', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreOrganization.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='meta', full_name='google.fhir.stu3.uscore.UsCoreOrganization.meta', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='implicit_rules', full_name='google.fhir.stu3.uscore.UsCoreOrganization.implicit_rules', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='language', full_name='google.fhir.stu3.uscore.UsCoreOrganization.language', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='text', full_name='google.fhir.stu3.uscore.UsCoreOrganization.text', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='contained', full_name='google.fhir.stu3.uscore.UsCoreOrganization.contained', index=5, number=6, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreOrganization.extension', index=6, number=7, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreOrganization.modifier_extension', index=7, number=8, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='identifier', full_name='google.fhir.stu3.uscore.UsCoreOrganization.identifier', index=8, number=9, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='active', full_name='google.fhir.stu3.uscore.UsCoreOrganization.active', index=9, number=10, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='type', full_name='google.fhir.stu3.uscore.UsCoreOrganization.type', index=10, number=11, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='name', full_name='google.fhir.stu3.uscore.UsCoreOrganization.name', index=11, number=12, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='alias', full_name='google.fhir.stu3.uscore.UsCoreOrganization.alias', index=12, number=13, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='telecom', full_name='google.fhir.stu3.uscore.UsCoreOrganization.telecom', index=13, number=14, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='address', full_name='google.fhir.stu3.uscore.UsCoreOrganization.address', index=14, number=15, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='part_of', full_name='google.fhir.stu3.uscore.UsCoreOrganization.part_of', index=15, number=16, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Organization'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='contact', full_name='google.fhir.stu3.uscore.UsCoreOrganization.contact', index=16, number=17, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='endpoint', full_name='google.fhir.stu3.uscore.UsCoreOrganization.endpoint', index=17, number=18, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0060http://hl7.org/fhir/StructureDefinition/Endpoint'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[_USCOREORGANIZATION_CONTACT, ], enum_types=[ ], serialized_options=_b('\300\237\343\266\005\003\232\265\216\223\0064http://hl7.org/fhir/StructureDefinition/Organization\262\376\344\227\006Dhttp://hl7.org/fhir/us/core/StructureDefinition/us-core-organization'), is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=47079, serialized_end=48735, ) _USCOREPATIENT_DECEASED = _descriptor.Descriptor( name='Deceased', full_name='google.fhir.stu3.uscore.UsCorePatient.Deceased', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='boolean', full_name='google.fhir.stu3.uscore.UsCorePatient.Deceased.boolean', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='date_time', full_name='google.fhir.stu3.uscore.UsCorePatient.Deceased.date_time', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name='deceased', full_name='google.fhir.stu3.uscore.UsCorePatient.Deceased.deceased', index=0, containing_type=None, fields=[]), ], serialized_start=50787, serialized_end=50916, ) _USCOREPATIENT_MULTIPLEBIRTH = _descriptor.Descriptor( name='MultipleBirth', full_name='google.fhir.stu3.uscore.UsCorePatient.MultipleBirth', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='boolean', full_name='google.fhir.stu3.uscore.UsCorePatient.MultipleBirth.boolean', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='integer', full_name='google.fhir.stu3.uscore.UsCorePatient.MultipleBirth.integer', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name='multiple_birth', full_name='google.fhir.stu3.uscore.UsCorePatient.MultipleBirth.multiple_birth', index=0, containing_type=None, fields=[]), ], serialized_start=50919, serialized_end=51056, ) _USCOREPATIENT_CONTACT = _descriptor.Descriptor( name='Contact', full_name='google.fhir.stu3.uscore.UsCorePatient.Contact', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCorePatient.Contact.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCorePatient.Contact.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCorePatient.Contact.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='relationship', full_name='google.fhir.stu3.uscore.UsCorePatient.Contact.relationship', index=3, number=4, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='name', full_name='google.fhir.stu3.uscore.UsCorePatient.Contact.name', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='telecom', full_name='google.fhir.stu3.uscore.UsCorePatient.Contact.telecom', index=5, number=6, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='address', full_name='google.fhir.stu3.uscore.UsCorePatient.Contact.address', index=6, number=7, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='gender', full_name='google.fhir.stu3.uscore.UsCorePatient.Contact.gender', index=7, number=8, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='organization', full_name='google.fhir.stu3.uscore.UsCorePatient.Contact.organization', index=8, number=9, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Organization'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='period', full_name='google.fhir.stu3.uscore.UsCorePatient.Contact.period', index=9, number=10, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=51059, serialized_end=51677, ) _USCOREPATIENT_COMMUNICATION = _descriptor.Descriptor( name='Communication', full_name='google.fhir.stu3.uscore.UsCorePatient.Communication', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCorePatient.Communication.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCorePatient.Communication.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCorePatient.Communication.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='language', full_name='google.fhir.stu3.uscore.UsCorePatient.Communication.language', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='preferred', full_name='google.fhir.stu3.uscore.UsCorePatient.Communication.preferred', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=51680, serialized_end=51975, ) _USCOREPATIENT_LINK = _descriptor.Descriptor( name='Link', full_name='google.fhir.stu3.uscore.UsCorePatient.Link', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCorePatient.Link.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCorePatient.Link.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCorePatient.Link.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='other', full_name='google.fhir.stu3.uscore.UsCorePatient.Link.other', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001\362\377\374\302\006/http://hl7.org/fhir/StructureDefinition/Patient\362\377\374\302\0065http://hl7.org/fhir/StructureDefinition/RelatedPerson'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='type', full_name='google.fhir.stu3.uscore.UsCorePatient.Link.type', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=51978, serialized_end=52376, ) _USCOREPATIENT = _descriptor.Descriptor( name='UsCorePatient', full_name='google.fhir.stu3.uscore.UsCorePatient', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCorePatient.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='meta', full_name='google.fhir.stu3.uscore.UsCorePatient.meta', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='implicit_rules', full_name='google.fhir.stu3.uscore.UsCorePatient.implicit_rules', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='language', full_name='google.fhir.stu3.uscore.UsCorePatient.language', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='text', full_name='google.fhir.stu3.uscore.UsCorePatient.text', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='contained', full_name='google.fhir.stu3.uscore.UsCorePatient.contained', index=5, number=6, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCorePatient.extension', index=6, number=7, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCorePatient.modifier_extension', index=7, number=8, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='identifier', full_name='google.fhir.stu3.uscore.UsCorePatient.identifier', index=8, number=9, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='active', full_name='google.fhir.stu3.uscore.UsCorePatient.active', index=9, number=10, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='name', full_name='google.fhir.stu3.uscore.UsCorePatient.name', index=10, number=11, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='telecom', full_name='google.fhir.stu3.uscore.UsCorePatient.telecom', index=11, number=12, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='gender', full_name='google.fhir.stu3.uscore.UsCorePatient.gender', index=12, number=13, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='birth_date', full_name='google.fhir.stu3.uscore.UsCorePatient.birth_date', index=13, number=14, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='deceased', full_name='google.fhir.stu3.uscore.UsCorePatient.deceased', index=14, number=15, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\370\341\343\311\005\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='address', full_name='google.fhir.stu3.uscore.UsCorePatient.address', index=15, number=16, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='marital_status', full_name='google.fhir.stu3.uscore.UsCorePatient.marital_status', index=16, number=17, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='multiple_birth', full_name='google.fhir.stu3.uscore.UsCorePatient.multiple_birth', index=17, number=18, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\370\341\343\311\005\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='photo', full_name='google.fhir.stu3.uscore.UsCorePatient.photo', index=18, number=19, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='contact', full_name='google.fhir.stu3.uscore.UsCorePatient.contact', index=19, number=20, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='communication', full_name='google.fhir.stu3.uscore.UsCorePatient.communication', index=20, number=22, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='general_practitioner', full_name='google.fhir.stu3.uscore.UsCorePatient.general_practitioner', index=21, number=23, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Organization\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Practitioner'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='managing_organization', full_name='google.fhir.stu3.uscore.UsCorePatient.managing_organization', index=22, number=24, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Organization'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='link', full_name='google.fhir.stu3.uscore.UsCorePatient.link', index=23, number=25, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='race', full_name='google.fhir.stu3.uscore.UsCorePatient.race', index=24, number=26, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\252\374\217\223\006<http://hl7.org/fhir/us/core/StructureDefinition/us-core-race'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='ethnicity', full_name='google.fhir.stu3.uscore.UsCorePatient.ethnicity', index=25, number=27, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\252\374\217\223\006Ahttp://hl7.org/fhir/us/core/StructureDefinition/us-core-ethnicity'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='birthsex', full_name='google.fhir.stu3.uscore.UsCorePatient.birthsex', index=26, number=28, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\252\374\217\223\006@http://hl7.org/fhir/us/core/StructureDefinition/us-core-birthsex'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[_USCOREPATIENT_DECEASED, _USCOREPATIENT_MULTIPLEBIRTH, _USCOREPATIENT_CONTACT, _USCOREPATIENT_COMMUNICATION, _USCOREPATIENT_LINK, ], enum_types=[ ], serialized_options=_b('\300\237\343\266\005\003\232\265\216\223\006/http://hl7.org/fhir/StructureDefinition/Patient\262\376\344\227\006?http://hl7.org/fhir/us/core/StructureDefinition/us-core-patient'), is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=48738, serialized_end=52507, ) _USCOREPRACTITIONER_QUALIFICATION = _descriptor.Descriptor( name='Qualification', full_name='google.fhir.stu3.uscore.UsCorePractitioner.Qualification', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCorePractitioner.Qualification.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCorePractitioner.Qualification.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCorePractitioner.Qualification.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='identifier', full_name='google.fhir.stu3.uscore.UsCorePractitioner.Qualification.identifier', index=3, number=4, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='code', full_name='google.fhir.stu3.uscore.UsCorePractitioner.Qualification.code', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='period', full_name='google.fhir.stu3.uscore.UsCorePractitioner.Qualification.period', index=5, number=6, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='issuer', full_name='google.fhir.stu3.uscore.UsCorePractitioner.Qualification.issuer', index=6, number=7, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Organization'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=53542, serialized_end=53996, ) _USCOREPRACTITIONER = _descriptor.Descriptor( name='UsCorePractitioner', full_name='google.fhir.stu3.uscore.UsCorePractitioner', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCorePractitioner.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='meta', full_name='google.fhir.stu3.uscore.UsCorePractitioner.meta', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='implicit_rules', full_name='google.fhir.stu3.uscore.UsCorePractitioner.implicit_rules', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='language', full_name='google.fhir.stu3.uscore.UsCorePractitioner.language', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='text', full_name='google.fhir.stu3.uscore.UsCorePractitioner.text', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='contained', full_name='google.fhir.stu3.uscore.UsCorePractitioner.contained', index=5, number=6, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCorePractitioner.extension', index=6, number=7, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCorePractitioner.modifier_extension', index=7, number=8, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='identifier', full_name='google.fhir.stu3.uscore.UsCorePractitioner.identifier', index=8, number=9, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='active', full_name='google.fhir.stu3.uscore.UsCorePractitioner.active', index=9, number=10, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='name', full_name='google.fhir.stu3.uscore.UsCorePractitioner.name', index=10, number=11, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='telecom', full_name='google.fhir.stu3.uscore.UsCorePractitioner.telecom', index=11, number=12, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='address', full_name='google.fhir.stu3.uscore.UsCorePractitioner.address', index=12, number=13, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='gender', full_name='google.fhir.stu3.uscore.UsCorePractitioner.gender', index=13, number=14, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='birth_date', full_name='google.fhir.stu3.uscore.UsCorePractitioner.birth_date', index=14, number=15, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='photo', full_name='google.fhir.stu3.uscore.UsCorePractitioner.photo', index=15, number=16, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='qualification', full_name='google.fhir.stu3.uscore.UsCorePractitioner.qualification', index=16, number=17, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='communication', full_name='google.fhir.stu3.uscore.UsCorePractitioner.communication', index=17, number=18, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[_USCOREPRACTITIONER_QUALIFICATION, ], enum_types=[ ], serialized_options=_b('\300\237\343\266\005\003\232\265\216\223\0064http://hl7.org/fhir/StructureDefinition/Practitioner\262\376\344\227\006Dhttp://hl7.org/fhir/us/core/StructureDefinition/us-core-practitioner'), is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=52510, serialized_end=54137, ) _USCOREPROCEDURE_PERFORMED = _descriptor.Descriptor( name='Performed', full_name='google.fhir.stu3.uscore.UsCoreProcedure.Performed', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='date_time', full_name='google.fhir.stu3.uscore.UsCoreProcedure.Performed.date_time', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='period', full_name='google.fhir.stu3.uscore.UsCoreProcedure.Performed.period', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name='performed', full_name='google.fhir.stu3.uscore.UsCoreProcedure.Performed.performed', index=0, containing_type=None, fields=[]), ], serialized_start=57349, serialized_end=57478, ) _USCOREPROCEDURE_PERFORMER = _descriptor.Descriptor( name='Performer', full_name='google.fhir.stu3.uscore.UsCoreProcedure.Performer', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreProcedure.Performer.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreProcedure.Performer.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreProcedure.Performer.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='role', full_name='google.fhir.stu3.uscore.UsCoreProcedure.Performer.role', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='actor', full_name='google.fhir.stu3.uscore.UsCoreProcedure.Performer.actor', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Practitioner\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Organization\362\377\374\302\006/http://hl7.org/fhir/StructureDefinition/Patient\362\377\374\302\0065http://hl7.org/fhir/StructureDefinition/RelatedPerson\362\377\374\302\006.http://hl7.org/fhir/StructureDefinition/Device'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='on_behalf_of', full_name='google.fhir.stu3.uscore.UsCoreProcedure.Performer.on_behalf_of', index=5, number=6, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Organization'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=57481, serialized_end=58165, ) _USCOREPROCEDURE_FOCALDEVICE = _descriptor.Descriptor( name='FocalDevice', full_name='google.fhir.stu3.uscore.UsCoreProcedure.FocalDevice', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreProcedure.FocalDevice.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreProcedure.FocalDevice.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreProcedure.FocalDevice.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='action', full_name='google.fhir.stu3.uscore.UsCoreProcedure.FocalDevice.action', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='manipulated', full_name='google.fhir.stu3.uscore.UsCoreProcedure.FocalDevice.manipulated', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001\362\377\374\302\006.http://hl7.org/fhir/StructureDefinition/Device'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=58168, serialized_end=58515, ) _USCOREPROCEDURE = _descriptor.Descriptor( name='UsCoreProcedure', full_name='google.fhir.stu3.uscore.UsCoreProcedure', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreProcedure.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='meta', full_name='google.fhir.stu3.uscore.UsCoreProcedure.meta', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='implicit_rules', full_name='google.fhir.stu3.uscore.UsCoreProcedure.implicit_rules', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='language', full_name='google.fhir.stu3.uscore.UsCoreProcedure.language', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='text', full_name='google.fhir.stu3.uscore.UsCoreProcedure.text', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='contained', full_name='google.fhir.stu3.uscore.UsCoreProcedure.contained', index=5, number=6, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreProcedure.extension', index=6, number=7, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreProcedure.modifier_extension', index=7, number=8, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='identifier', full_name='google.fhir.stu3.uscore.UsCoreProcedure.identifier', index=8, number=9, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='definition', full_name='google.fhir.stu3.uscore.UsCoreProcedure.definition', index=9, number=10, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0066http://hl7.org/fhir/StructureDefinition/PlanDefinition\362\377\374\302\006:http://hl7.org/fhir/StructureDefinition/ActivityDefinition\362\377\374\302\0069http://hl7.org/fhir/StructureDefinition/HealthcareService'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='based_on', full_name='google.fhir.stu3.uscore.UsCoreProcedure.based_on', index=10, number=11, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0060http://hl7.org/fhir/StructureDefinition/CarePlan\362\377\374\302\0068http://hl7.org/fhir/StructureDefinition/ProcedureRequest\362\377\374\302\0067http://hl7.org/fhir/StructureDefinition/ReferralRequest'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='part_of', full_name='google.fhir.stu3.uscore.UsCoreProcedure.part_of', index=11, number=12, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0061http://hl7.org/fhir/StructureDefinition/Procedure\362\377\374\302\0063http://hl7.org/fhir/StructureDefinition/Observation\362\377\374\302\006@http://hl7.org/fhir/StructureDefinition/MedicationAdministration'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='status', full_name='google.fhir.stu3.uscore.UsCoreProcedure.status', index=12, number=13, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='not_done', full_name='google.fhir.stu3.uscore.UsCoreProcedure.not_done', index=13, number=14, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='not_done_reason', full_name='google.fhir.stu3.uscore.UsCoreProcedure.not_done_reason', index=14, number=15, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='category', full_name='google.fhir.stu3.uscore.UsCoreProcedure.category', index=15, number=16, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='code', full_name='google.fhir.stu3.uscore.UsCoreProcedure.code', index=16, number=17, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='subject', full_name='google.fhir.stu3.uscore.UsCoreProcedure.subject', index=17, number=18, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001\362\377\374\302\006?http://hl7.org/fhir/us/core/StructureDefinition/us-core-patient'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='context', full_name='google.fhir.stu3.uscore.UsCoreProcedure.context', index=18, number=19, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0061http://hl7.org/fhir/StructureDefinition/Encounter\362\377\374\302\0065http://hl7.org/fhir/StructureDefinition/EpisodeOfCare'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='performed', full_name='google.fhir.stu3.uscore.UsCoreProcedure.performed', index=19, number=20, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\370\341\343\311\005\001\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='performer', full_name='google.fhir.stu3.uscore.UsCoreProcedure.performer', index=20, number=21, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='location', full_name='google.fhir.stu3.uscore.UsCoreProcedure.location', index=21, number=22, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0060http://hl7.org/fhir/StructureDefinition/Location'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='reason_code', full_name='google.fhir.stu3.uscore.UsCoreProcedure.reason_code', index=22, number=23, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='reason_reference', full_name='google.fhir.stu3.uscore.UsCoreProcedure.reason_reference', index=23, number=24, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0061http://hl7.org/fhir/StructureDefinition/Condition\362\377\374\302\0063http://hl7.org/fhir/StructureDefinition/Observation'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='body_site', full_name='google.fhir.stu3.uscore.UsCoreProcedure.body_site', index=24, number=25, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='outcome', full_name='google.fhir.stu3.uscore.UsCoreProcedure.outcome', index=25, number=26, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='report', full_name='google.fhir.stu3.uscore.UsCoreProcedure.report', index=26, number=27, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0068http://hl7.org/fhir/StructureDefinition/DiagnosticReport'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='complication', full_name='google.fhir.stu3.uscore.UsCoreProcedure.complication', index=27, number=28, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='complication_detail', full_name='google.fhir.stu3.uscore.UsCoreProcedure.complication_detail', index=28, number=29, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0061http://hl7.org/fhir/StructureDefinition/Condition'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='follow_up', full_name='google.fhir.stu3.uscore.UsCoreProcedure.follow_up', index=29, number=30, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='note', full_name='google.fhir.stu3.uscore.UsCoreProcedure.note', index=30, number=31, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='focal_device', full_name='google.fhir.stu3.uscore.UsCoreProcedure.focal_device', index=31, number=32, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='used_reference', full_name='google.fhir.stu3.uscore.UsCoreProcedure.used_reference', index=32, number=33, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\006.http://hl7.org/fhir/StructureDefinition/Device\362\377\374\302\0062http://hl7.org/fhir/StructureDefinition/Medication\362\377\374\302\0061http://hl7.org/fhir/StructureDefinition/Substance'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='used_code', full_name='google.fhir.stu3.uscore.UsCoreProcedure.used_code', index=33, number=34, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[_USCOREPROCEDURE_PERFORMED, _USCOREPROCEDURE_PERFORMER, _USCOREPROCEDURE_FOCALDEVICE, ], enum_types=[ ], serialized_options=_b('\300\237\343\266\005\003\232\265\216\223\0061http://hl7.org/fhir/StructureDefinition/Procedure\262\376\344\227\006Ahttp://hl7.org/fhir/us/core/StructureDefinition/us-core-procedure'), is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=54140, serialized_end=58650, ) _CAPABILITYSTATEMENTPROFILERESOURCEASSOCIATIONEXTENSION = _descriptor.Descriptor( name='CapabilityStatementProfileResourceAssociationExtension', full_name='google.fhir.stu3.uscore.CapabilityStatementProfileResourceAssociationExtension', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.CapabilityStatementProfileResourceAssociationExtension.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.CapabilityStatementProfileResourceAssociationExtension.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='value_code', full_name='google.fhir.stu3.uscore.CapabilityStatementProfileResourceAssociationExtension.value_code', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=_b('\300\237\343\266\005\002\232\265\216\223\0061http://hl7.org/fhir/StructureDefinition/Extension\262\376\344\227\006Dhttp://hl7.org/fhir/us/core/StructureDefinition/us-core-profile-link'), is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=58653, serialized_end=59007, ) _PATIENTUSCORERACEEXTENSION = _descriptor.Descriptor( name='PatientUSCoreRaceExtension', full_name='google.fhir.stu3.uscore.PatientUSCoreRaceExtension', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.PatientUSCoreRaceExtension.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.PatientUSCoreRaceExtension.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='omb_category', full_name='google.fhir.stu3.uscore.PatientUSCoreRaceExtension.omb_category', index=2, number=4, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='detailed', full_name='google.fhir.stu3.uscore.PatientUSCoreRaceExtension.detailed', index=3, number=5, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='text', full_name='google.fhir.stu3.uscore.PatientUSCoreRaceExtension.text', index=4, number=6, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=_b('\300\237\343\266\005\002\232\265\216\223\0061http://hl7.org/fhir/StructureDefinition/Extension\262\376\344\227\006<http://hl7.org/fhir/us/core/StructureDefinition/us-core-race'), is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=59010, serialized_end=59423, ) _USCORESMOKINGSTATUS_EFFECTIVE = _descriptor.Descriptor( name='Effective', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Effective', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='date_time', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Effective.date_time', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='period', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Effective.period', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name='effective', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Effective.effective', index=0, containing_type=None, fields=[]), ], serialized_start=19796, serialized_end=19925, ) _USCORESMOKINGSTATUS_VALUE = _descriptor.Descriptor( name='Value', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Value', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='codeable_concept', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Value.codeable_concept', index=0, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name='value', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Value.value', index=0, containing_type=None, fields=[]), ], serialized_start=62349, serialized_end=62434, ) _USCORESMOKINGSTATUS_REFERENCERANGE = _descriptor.Descriptor( name='ReferenceRange', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.ReferenceRange', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.ReferenceRange.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.ReferenceRange.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.ReferenceRange.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='low', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.ReferenceRange.low', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='high', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.ReferenceRange.high', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='type', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.ReferenceRange.type', index=5, number=6, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='applies_to', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.ReferenceRange.applies_to', index=6, number=7, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='age', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.ReferenceRange.age', index=7, number=8, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='text', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.ReferenceRange.text', index=8, number=9, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=44832, serialized_end=45322, ) _USCORESMOKINGSTATUS_RELATED = _descriptor.Descriptor( name='Related', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Related', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Related.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Related.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Related.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='type', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Related.type', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='target', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Related.target', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001\362\377\374\302\0063http://hl7.org/fhir/StructureDefinition/Observation\362\377\374\302\006=http://hl7.org/fhir/StructureDefinition/QuestionnaireResponse\362\377\374\302\0060http://hl7.org/fhir/StructureDefinition/Sequence'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=45325, serialized_end=45805, ) _USCORESMOKINGSTATUS_COMPONENT_VALUE = _descriptor.Descriptor( name='Value', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Component.Value', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='quantity', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Component.Value.quantity', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='codeable_concept', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Component.Value.codeable_concept', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='string_value', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Component.Value.string_value', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, json_name='string', file=DESCRIPTOR), _descriptor.FieldDescriptor( name='range', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Component.Value.range', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='ratio', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Component.Value.ratio', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='sampled_data', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Component.Value.sampled_data', index=5, number=6, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='attachment', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Component.Value.attachment', index=6, number=7, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='time', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Component.Value.time', index=7, number=8, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='date_time', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Component.Value.date_time', index=8, number=9, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='period', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Component.Value.period', index=9, number=10, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name='value', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Component.Value.value', index=0, containing_type=None, fields=[]), ], serialized_start=46361, serialized_end=46930, ) _USCORESMOKINGSTATUS_COMPONENT = _descriptor.Descriptor( name='Component', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Component', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Component.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Component.extension', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Component.modifier_extension', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='code', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Component.code', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='value', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Component.value', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\370\341\343\311\005\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='data_absent_reason', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Component.data_absent_reason', index=5, number=6, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='interpretation', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Component.interpretation', index=6, number=7, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='reference_range', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.Component.reference_range', index=7, number=8, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[_USCORESMOKINGSTATUS_COMPONENT_VALUE, ], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=63413, serialized_end=64525, ) _USCORESMOKINGSTATUS = _descriptor.Descriptor( name='UsCoreSmokingstatus', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='meta', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.meta', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='implicit_rules', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.implicit_rules', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='language', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.language', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='text', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.text', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='contained', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.contained', index=5, number=6, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='extension', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.extension', index=6, number=7, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='modifier_extension', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.modifier_extension', index=7, number=8, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='identifier', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.identifier', index=8, number=9, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='based_on', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.based_on', index=9, number=10, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0060http://hl7.org/fhir/StructureDefinition/CarePlan\362\377\374\302\0065http://hl7.org/fhir/StructureDefinition/DeviceRequest\362\377\374\302\006Bhttp://hl7.org/fhir/StructureDefinition/ImmunizationRecommendation\362\377\374\302\0069http://hl7.org/fhir/StructureDefinition/MedicationRequest\362\377\374\302\0066http://hl7.org/fhir/StructureDefinition/NutritionOrder\362\377\374\302\0068http://hl7.org/fhir/StructureDefinition/ProcedureRequest\362\377\374\302\0067http://hl7.org/fhir/StructureDefinition/ReferralRequest'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='status', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.status', index=10, number=11, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='category', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.category', index=11, number=12, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='code', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.code', index=12, number=13, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='subject', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.subject', index=13, number=14, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001\362\377\374\302\006?http://hl7.org/fhir/us/core/StructureDefinition/us-core-patient'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='context', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.context', index=14, number=15, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0061http://hl7.org/fhir/StructureDefinition/Encounter\362\377\374\302\0065http://hl7.org/fhir/StructureDefinition/EpisodeOfCare'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='effective', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.effective', index=15, number=16, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\370\341\343\311\005\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='issued', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.issued', index=16, number=17, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='performer', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.performer', index=17, number=18, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Practitioner\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/Organization\362\377\374\302\006/http://hl7.org/fhir/StructureDefinition/Patient\362\377\374\302\0065http://hl7.org/fhir/StructureDefinition/RelatedPerson'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='value', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.value', index=18, number=19, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\370\341\343\311\005\001\360\320\207\353\004\001'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='data_absent_reason', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.data_absent_reason', index=19, number=20, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='interpretation', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.interpretation', index=20, number=21, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='comment', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.comment', index=21, number=22, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='body_site', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.body_site', index=22, number=23, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='method', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.method', index=23, number=24, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='specimen', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.specimen', index=24, number=25, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\0060http://hl7.org/fhir/StructureDefinition/Specimen'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='device', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.device', index=25, number=26, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\362\377\374\302\006.http://hl7.org/fhir/StructureDefinition/Device\362\377\374\302\0064http://hl7.org/fhir/StructureDefinition/DeviceMetric'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='reference_range', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.reference_range', index=26, number=27, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='related', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.related', index=27, number=28, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='component', full_name='google.fhir.stu3.uscore.UsCoreSmokingstatus.component', index=28, number=29, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[_USCORESMOKINGSTATUS_EFFECTIVE, _USCORESMOKINGSTATUS_VALUE, _USCORESMOKINGSTATUS_REFERENCERANGE, _USCORESMOKINGSTATUS_RELATED, _USCORESMOKINGSTATUS_COMPONENT, ], enum_types=[ ], serialized_options=_b('\300\237\343\266\005\003\232\265\216\223\0063http://hl7.org/fhir/StructureDefinition/Observation\262\376\344\227\006Ehttp://hl7.org/fhir/us/core/StructureDefinition/us-core-smokingstatus'), is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=59426, serialized_end=64666, ) _USCOREALLERGYINTOLERANCE_ONSET.fields_by_name['date_time'].message_type = proto_dot_stu3_dot_datatypes__pb2._DATETIME _USCOREALLERGYINTOLERANCE_ONSET.fields_by_name['age'].message_type = proto_dot_stu3_dot_datatypes__pb2._AGE _USCOREALLERGYINTOLERANCE_ONSET.fields_by_name['period'].message_type = proto_dot_stu3_dot_datatypes__pb2._PERIOD _USCOREALLERGYINTOLERANCE_ONSET.fields_by_name['range'].message_type = proto_dot_stu3_dot_datatypes__pb2._RANGE _USCOREALLERGYINTOLERANCE_ONSET.fields_by_name['string_value'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREALLERGYINTOLERANCE_ONSET.containing_type = _USCOREALLERGYINTOLERANCE _USCOREALLERGYINTOLERANCE_ONSET.oneofs_by_name['onset'].fields.append( _USCOREALLERGYINTOLERANCE_ONSET.fields_by_name['date_time']) _USCOREALLERGYINTOLERANCE_ONSET.fields_by_name['date_time'].containing_oneof = _USCOREALLERGYINTOLERANCE_ONSET.oneofs_by_name['onset'] _USCOREALLERGYINTOLERANCE_ONSET.oneofs_by_name['onset'].fields.append( _USCOREALLERGYINTOLERANCE_ONSET.fields_by_name['age']) _USCOREALLERGYINTOLERANCE_ONSET.fields_by_name['age'].containing_oneof = _USCOREALLERGYINTOLERANCE_ONSET.oneofs_by_name['onset'] _USCOREALLERGYINTOLERANCE_ONSET.oneofs_by_name['onset'].fields.append( _USCOREALLERGYINTOLERANCE_ONSET.fields_by_name['period']) _USCOREALLERGYINTOLERANCE_ONSET.fields_by_name['period'].containing_oneof = _USCOREALLERGYINTOLERANCE_ONSET.oneofs_by_name['onset'] _USCOREALLERGYINTOLERANCE_ONSET.oneofs_by_name['onset'].fields.append( _USCOREALLERGYINTOLERANCE_ONSET.fields_by_name['range']) _USCOREALLERGYINTOLERANCE_ONSET.fields_by_name['range'].containing_oneof = _USCOREALLERGYINTOLERANCE_ONSET.oneofs_by_name['onset'] _USCOREALLERGYINTOLERANCE_ONSET.oneofs_by_name['onset'].fields.append( _USCOREALLERGYINTOLERANCE_ONSET.fields_by_name['string_value']) _USCOREALLERGYINTOLERANCE_ONSET.fields_by_name['string_value'].containing_oneof = _USCOREALLERGYINTOLERANCE_ONSET.oneofs_by_name['onset'] _USCOREALLERGYINTOLERANCE_REACTION.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREALLERGYINTOLERANCE_REACTION.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREALLERGYINTOLERANCE_REACTION.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREALLERGYINTOLERANCE_REACTION.fields_by_name['substance'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREALLERGYINTOLERANCE_REACTION.fields_by_name['manifestation'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREALLERGYINTOLERANCE_REACTION.fields_by_name['description'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREALLERGYINTOLERANCE_REACTION.fields_by_name['onset'].message_type = proto_dot_stu3_dot_datatypes__pb2._DATETIME _USCOREALLERGYINTOLERANCE_REACTION.fields_by_name['severity'].message_type = proto_dot_stu3_dot_codes__pb2._ALLERGYINTOLERANCESEVERITYCODE _USCOREALLERGYINTOLERANCE_REACTION.fields_by_name['exposure_route'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREALLERGYINTOLERANCE_REACTION.fields_by_name['note'].message_type = proto_dot_stu3_dot_datatypes__pb2._ANNOTATION _USCOREALLERGYINTOLERANCE_REACTION.containing_type = _USCOREALLERGYINTOLERANCE _USCOREALLERGYINTOLERANCE.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._ID _USCOREALLERGYINTOLERANCE.fields_by_name['meta'].message_type = proto_dot_stu3_dot_datatypes__pb2._META _USCOREALLERGYINTOLERANCE.fields_by_name['implicit_rules'].message_type = proto_dot_stu3_dot_datatypes__pb2._URI _USCOREALLERGYINTOLERANCE.fields_by_name['language'].message_type = proto_dot_stu3_dot_datatypes__pb2._LANGUAGECODE _USCOREALLERGYINTOLERANCE.fields_by_name['text'].message_type = proto_dot_stu3_dot_metadatatypes__pb2._NARRATIVE _USCOREALLERGYINTOLERANCE.fields_by_name['contained'].message_type = proto_dot_stu3_dot_resources__pb2._CONTAINEDRESOURCE _USCOREALLERGYINTOLERANCE.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREALLERGYINTOLERANCE.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREALLERGYINTOLERANCE.fields_by_name['identifier'].message_type = proto_dot_stu3_dot_datatypes__pb2._IDENTIFIER _USCOREALLERGYINTOLERANCE.fields_by_name['clinical_status'].message_type = proto_dot_stu3_dot_codes__pb2._ALLERGYINTOLERANCECLINICALSTATUSCODE _USCOREALLERGYINTOLERANCE.fields_by_name['verification_status'].message_type = proto_dot_stu3_dot_codes__pb2._ALLERGYINTOLERANCEVERIFICATIONSTATUSCODE _USCOREALLERGYINTOLERANCE.fields_by_name['type'].message_type = proto_dot_stu3_dot_codes__pb2._ALLERGYINTOLERANCETYPECODE _USCOREALLERGYINTOLERANCE.fields_by_name['category'].message_type = proto_dot_stu3_dot_codes__pb2._ALLERGYINTOLERANCECATEGORYCODE _USCOREALLERGYINTOLERANCE.fields_by_name['criticality'].message_type = proto_dot_stu3_dot_codes__pb2._ALLERGYINTOLERANCECRITICALITYCODE _USCOREALLERGYINTOLERANCE.fields_by_name['code'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREALLERGYINTOLERANCE.fields_by_name['patient'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREALLERGYINTOLERANCE.fields_by_name['onset'].message_type = _USCOREALLERGYINTOLERANCE_ONSET _USCOREALLERGYINTOLERANCE.fields_by_name['asserted_date'].message_type = proto_dot_stu3_dot_datatypes__pb2._DATETIME _USCOREALLERGYINTOLERANCE.fields_by_name['recorder'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREALLERGYINTOLERANCE.fields_by_name['asserter'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREALLERGYINTOLERANCE.fields_by_name['last_occurrence'].message_type = proto_dot_stu3_dot_datatypes__pb2._DATETIME _USCOREALLERGYINTOLERANCE.fields_by_name['note'].message_type = proto_dot_stu3_dot_datatypes__pb2._ANNOTATION _USCOREALLERGYINTOLERANCE.fields_by_name['reaction'].message_type = _USCOREALLERGYINTOLERANCE_REACTION _PATIENTUSCOREBIRTHSEXEXTENSION.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _PATIENTUSCOREBIRTHSEXEXTENSION.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _PATIENTUSCOREBIRTHSEXEXTENSION.fields_by_name['value_code'].message_type = proto_dot_stu3_dot_uscore__codes__pb2._USCOREBIRTHSEXCODE _USCORECAREPLAN_ACTIVITY_DETAIL_SCHEDULED.fields_by_name['timing'].message_type = proto_dot_stu3_dot_datatypes__pb2._TIMING _USCORECAREPLAN_ACTIVITY_DETAIL_SCHEDULED.fields_by_name['period'].message_type = proto_dot_stu3_dot_datatypes__pb2._PERIOD _USCORECAREPLAN_ACTIVITY_DETAIL_SCHEDULED.fields_by_name['string_value'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCORECAREPLAN_ACTIVITY_DETAIL_SCHEDULED.containing_type = _USCORECAREPLAN_ACTIVITY_DETAIL _USCORECAREPLAN_ACTIVITY_DETAIL_SCHEDULED.oneofs_by_name['scheduled'].fields.append( _USCORECAREPLAN_ACTIVITY_DETAIL_SCHEDULED.fields_by_name['timing']) _USCORECAREPLAN_ACTIVITY_DETAIL_SCHEDULED.fields_by_name['timing'].containing_oneof = _USCORECAREPLAN_ACTIVITY_DETAIL_SCHEDULED.oneofs_by_name['scheduled'] _USCORECAREPLAN_ACTIVITY_DETAIL_SCHEDULED.oneofs_by_name['scheduled'].fields.append( _USCORECAREPLAN_ACTIVITY_DETAIL_SCHEDULED.fields_by_name['period']) _USCORECAREPLAN_ACTIVITY_DETAIL_SCHEDULED.fields_by_name['period'].containing_oneof = _USCORECAREPLAN_ACTIVITY_DETAIL_SCHEDULED.oneofs_by_name['scheduled'] _USCORECAREPLAN_ACTIVITY_DETAIL_SCHEDULED.oneofs_by_name['scheduled'].fields.append( _USCORECAREPLAN_ACTIVITY_DETAIL_SCHEDULED.fields_by_name['string_value']) _USCORECAREPLAN_ACTIVITY_DETAIL_SCHEDULED.fields_by_name['string_value'].containing_oneof = _USCORECAREPLAN_ACTIVITY_DETAIL_SCHEDULED.oneofs_by_name['scheduled'] _USCORECAREPLAN_ACTIVITY_DETAIL_PRODUCT.fields_by_name['codeable_concept'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCORECAREPLAN_ACTIVITY_DETAIL_PRODUCT.fields_by_name['reference'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORECAREPLAN_ACTIVITY_DETAIL_PRODUCT.containing_type = _USCORECAREPLAN_ACTIVITY_DETAIL _USCORECAREPLAN_ACTIVITY_DETAIL_PRODUCT.oneofs_by_name['product'].fields.append( _USCORECAREPLAN_ACTIVITY_DETAIL_PRODUCT.fields_by_name['codeable_concept']) _USCORECAREPLAN_ACTIVITY_DETAIL_PRODUCT.fields_by_name['codeable_concept'].containing_oneof = _USCORECAREPLAN_ACTIVITY_DETAIL_PRODUCT.oneofs_by_name['product'] _USCORECAREPLAN_ACTIVITY_DETAIL_PRODUCT.oneofs_by_name['product'].fields.append( _USCORECAREPLAN_ACTIVITY_DETAIL_PRODUCT.fields_by_name['reference']) _USCORECAREPLAN_ACTIVITY_DETAIL_PRODUCT.fields_by_name['reference'].containing_oneof = _USCORECAREPLAN_ACTIVITY_DETAIL_PRODUCT.oneofs_by_name['product'] _USCORECAREPLAN_ACTIVITY_DETAIL.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCORECAREPLAN_ACTIVITY_DETAIL.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCORECAREPLAN_ACTIVITY_DETAIL.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCORECAREPLAN_ACTIVITY_DETAIL.fields_by_name['category'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCORECAREPLAN_ACTIVITY_DETAIL.fields_by_name['definition'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORECAREPLAN_ACTIVITY_DETAIL.fields_by_name['code'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCORECAREPLAN_ACTIVITY_DETAIL.fields_by_name['reason_code'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCORECAREPLAN_ACTIVITY_DETAIL.fields_by_name['reason_reference'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORECAREPLAN_ACTIVITY_DETAIL.fields_by_name['goal'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORECAREPLAN_ACTIVITY_DETAIL.fields_by_name['status'].message_type = proto_dot_stu3_dot_codes__pb2._CAREPLANACTIVITYSTATUSCODE _USCORECAREPLAN_ACTIVITY_DETAIL.fields_by_name['status_reason'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCORECAREPLAN_ACTIVITY_DETAIL.fields_by_name['prohibited'].message_type = proto_dot_stu3_dot_datatypes__pb2._BOOLEAN _USCORECAREPLAN_ACTIVITY_DETAIL.fields_by_name['scheduled'].message_type = _USCORECAREPLAN_ACTIVITY_DETAIL_SCHEDULED _USCORECAREPLAN_ACTIVITY_DETAIL.fields_by_name['location'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORECAREPLAN_ACTIVITY_DETAIL.fields_by_name['performer'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORECAREPLAN_ACTIVITY_DETAIL.fields_by_name['product'].message_type = _USCORECAREPLAN_ACTIVITY_DETAIL_PRODUCT _USCORECAREPLAN_ACTIVITY_DETAIL.fields_by_name['daily_amount'].message_type = proto_dot_stu3_dot_datatypes__pb2._SIMPLEQUANTITY _USCORECAREPLAN_ACTIVITY_DETAIL.fields_by_name['quantity'].message_type = proto_dot_stu3_dot_datatypes__pb2._SIMPLEQUANTITY _USCORECAREPLAN_ACTIVITY_DETAIL.fields_by_name['description'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCORECAREPLAN_ACTIVITY_DETAIL.containing_type = _USCORECAREPLAN_ACTIVITY _USCORECAREPLAN_ACTIVITY.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCORECAREPLAN_ACTIVITY.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCORECAREPLAN_ACTIVITY.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCORECAREPLAN_ACTIVITY.fields_by_name['outcome_codeable_concept'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCORECAREPLAN_ACTIVITY.fields_by_name['outcome_reference'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORECAREPLAN_ACTIVITY.fields_by_name['progress'].message_type = proto_dot_stu3_dot_datatypes__pb2._ANNOTATION _USCORECAREPLAN_ACTIVITY.fields_by_name['reference'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORECAREPLAN_ACTIVITY.fields_by_name['detail'].message_type = _USCORECAREPLAN_ACTIVITY_DETAIL _USCORECAREPLAN_ACTIVITY.containing_type = _USCORECAREPLAN _USCORECAREPLAN.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._ID _USCORECAREPLAN.fields_by_name['meta'].message_type = proto_dot_stu3_dot_datatypes__pb2._META _USCORECAREPLAN.fields_by_name['implicit_rules'].message_type = proto_dot_stu3_dot_datatypes__pb2._URI _USCORECAREPLAN.fields_by_name['language'].message_type = proto_dot_stu3_dot_datatypes__pb2._LANGUAGECODE _USCORECAREPLAN.fields_by_name['text'].message_type = proto_dot_stu3_dot_metadatatypes__pb2._NARRATIVE _USCORECAREPLAN.fields_by_name['contained'].message_type = proto_dot_stu3_dot_resources__pb2._CONTAINEDRESOURCE _USCORECAREPLAN.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCORECAREPLAN.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCORECAREPLAN.fields_by_name['identifier'].message_type = proto_dot_stu3_dot_datatypes__pb2._IDENTIFIER _USCORECAREPLAN.fields_by_name['definition'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORECAREPLAN.fields_by_name['based_on'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORECAREPLAN.fields_by_name['replaces'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORECAREPLAN.fields_by_name['part_of'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORECAREPLAN.fields_by_name['status'].message_type = proto_dot_stu3_dot_codes__pb2._CAREPLANSTATUSCODE _USCORECAREPLAN.fields_by_name['intent'].message_type = proto_dot_stu3_dot_codes__pb2._CAREPLANINTENTCODE _USCORECAREPLAN.fields_by_name['category'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCORECAREPLAN.fields_by_name['title'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCORECAREPLAN.fields_by_name['description'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCORECAREPLAN.fields_by_name['subject'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORECAREPLAN.fields_by_name['context'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORECAREPLAN.fields_by_name['period'].message_type = proto_dot_stu3_dot_datatypes__pb2._PERIOD _USCORECAREPLAN.fields_by_name['author'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORECAREPLAN.fields_by_name['care_team'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORECAREPLAN.fields_by_name['addresses'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORECAREPLAN.fields_by_name['supporting_info'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORECAREPLAN.fields_by_name['goal'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORECAREPLAN.fields_by_name['activity'].message_type = _USCORECAREPLAN_ACTIVITY _USCORECAREPLAN.fields_by_name['note'].message_type = proto_dot_stu3_dot_datatypes__pb2._ANNOTATION _USCORECARETEAM_PARTICIPANT.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCORECARETEAM_PARTICIPANT.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCORECARETEAM_PARTICIPANT.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCORECARETEAM_PARTICIPANT.fields_by_name['role'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCORECARETEAM_PARTICIPANT.fields_by_name['member'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORECARETEAM_PARTICIPANT.fields_by_name['on_behalf_of'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORECARETEAM_PARTICIPANT.fields_by_name['period'].message_type = proto_dot_stu3_dot_datatypes__pb2._PERIOD _USCORECARETEAM_PARTICIPANT.containing_type = _USCORECARETEAM _USCORECARETEAM.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._ID _USCORECARETEAM.fields_by_name['meta'].message_type = proto_dot_stu3_dot_datatypes__pb2._META _USCORECARETEAM.fields_by_name['implicit_rules'].message_type = proto_dot_stu3_dot_datatypes__pb2._URI _USCORECARETEAM.fields_by_name['language'].message_type = proto_dot_stu3_dot_datatypes__pb2._LANGUAGECODE _USCORECARETEAM.fields_by_name['text'].message_type = proto_dot_stu3_dot_metadatatypes__pb2._NARRATIVE _USCORECARETEAM.fields_by_name['contained'].message_type = proto_dot_stu3_dot_resources__pb2._CONTAINEDRESOURCE _USCORECARETEAM.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCORECARETEAM.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCORECARETEAM.fields_by_name['identifier'].message_type = proto_dot_stu3_dot_datatypes__pb2._IDENTIFIER _USCORECARETEAM.fields_by_name['status'].message_type = proto_dot_stu3_dot_codes__pb2._CARETEAMSTATUSCODE _USCORECARETEAM.fields_by_name['category'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCORECARETEAM.fields_by_name['name'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCORECARETEAM.fields_by_name['subject'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORECARETEAM.fields_by_name['context'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORECARETEAM.fields_by_name['period'].message_type = proto_dot_stu3_dot_datatypes__pb2._PERIOD _USCORECARETEAM.fields_by_name['participant'].message_type = _USCORECARETEAM_PARTICIPANT _USCORECARETEAM.fields_by_name['reason_code'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCORECARETEAM.fields_by_name['reason_reference'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORECARETEAM.fields_by_name['managing_organization'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORECARETEAM.fields_by_name['note'].message_type = proto_dot_stu3_dot_datatypes__pb2._ANNOTATION _USCORECONDITION_ONSET.fields_by_name['date_time'].message_type = proto_dot_stu3_dot_datatypes__pb2._DATETIME _USCORECONDITION_ONSET.fields_by_name['age'].message_type = proto_dot_stu3_dot_datatypes__pb2._AGE _USCORECONDITION_ONSET.fields_by_name['period'].message_type = proto_dot_stu3_dot_datatypes__pb2._PERIOD _USCORECONDITION_ONSET.fields_by_name['range'].message_type = proto_dot_stu3_dot_datatypes__pb2._RANGE _USCORECONDITION_ONSET.fields_by_name['string_value'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCORECONDITION_ONSET.containing_type = _USCORECONDITION _USCORECONDITION_ONSET.oneofs_by_name['onset'].fields.append( _USCORECONDITION_ONSET.fields_by_name['date_time']) _USCORECONDITION_ONSET.fields_by_name['date_time'].containing_oneof = _USCORECONDITION_ONSET.oneofs_by_name['onset'] _USCORECONDITION_ONSET.oneofs_by_name['onset'].fields.append( _USCORECONDITION_ONSET.fields_by_name['age']) _USCORECONDITION_ONSET.fields_by_name['age'].containing_oneof = _USCORECONDITION_ONSET.oneofs_by_name['onset'] _USCORECONDITION_ONSET.oneofs_by_name['onset'].fields.append( _USCORECONDITION_ONSET.fields_by_name['period']) _USCORECONDITION_ONSET.fields_by_name['period'].containing_oneof = _USCORECONDITION_ONSET.oneofs_by_name['onset'] _USCORECONDITION_ONSET.oneofs_by_name['onset'].fields.append( _USCORECONDITION_ONSET.fields_by_name['range']) _USCORECONDITION_ONSET.fields_by_name['range'].containing_oneof = _USCORECONDITION_ONSET.oneofs_by_name['onset'] _USCORECONDITION_ONSET.oneofs_by_name['onset'].fields.append( _USCORECONDITION_ONSET.fields_by_name['string_value']) _USCORECONDITION_ONSET.fields_by_name['string_value'].containing_oneof = _USCORECONDITION_ONSET.oneofs_by_name['onset'] _USCORECONDITION_ABATEMENT.fields_by_name['date_time'].message_type = proto_dot_stu3_dot_datatypes__pb2._DATETIME _USCORECONDITION_ABATEMENT.fields_by_name['age'].message_type = proto_dot_stu3_dot_datatypes__pb2._AGE _USCORECONDITION_ABATEMENT.fields_by_name['boolean'].message_type = proto_dot_stu3_dot_datatypes__pb2._BOOLEAN _USCORECONDITION_ABATEMENT.fields_by_name['period'].message_type = proto_dot_stu3_dot_datatypes__pb2._PERIOD _USCORECONDITION_ABATEMENT.fields_by_name['range'].message_type = proto_dot_stu3_dot_datatypes__pb2._RANGE _USCORECONDITION_ABATEMENT.fields_by_name['string_value'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCORECONDITION_ABATEMENT.containing_type = _USCORECONDITION _USCORECONDITION_ABATEMENT.oneofs_by_name['abatement'].fields.append( _USCORECONDITION_ABATEMENT.fields_by_name['date_time']) _USCORECONDITION_ABATEMENT.fields_by_name['date_time'].containing_oneof = _USCORECONDITION_ABATEMENT.oneofs_by_name['abatement'] _USCORECONDITION_ABATEMENT.oneofs_by_name['abatement'].fields.append( _USCORECONDITION_ABATEMENT.fields_by_name['age']) _USCORECONDITION_ABATEMENT.fields_by_name['age'].containing_oneof = _USCORECONDITION_ABATEMENT.oneofs_by_name['abatement'] _USCORECONDITION_ABATEMENT.oneofs_by_name['abatement'].fields.append( _USCORECONDITION_ABATEMENT.fields_by_name['boolean']) _USCORECONDITION_ABATEMENT.fields_by_name['boolean'].containing_oneof = _USCORECONDITION_ABATEMENT.oneofs_by_name['abatement'] _USCORECONDITION_ABATEMENT.oneofs_by_name['abatement'].fields.append( _USCORECONDITION_ABATEMENT.fields_by_name['period']) _USCORECONDITION_ABATEMENT.fields_by_name['period'].containing_oneof = _USCORECONDITION_ABATEMENT.oneofs_by_name['abatement'] _USCORECONDITION_ABATEMENT.oneofs_by_name['abatement'].fields.append( _USCORECONDITION_ABATEMENT.fields_by_name['range']) _USCORECONDITION_ABATEMENT.fields_by_name['range'].containing_oneof = _USCORECONDITION_ABATEMENT.oneofs_by_name['abatement'] _USCORECONDITION_ABATEMENT.oneofs_by_name['abatement'].fields.append( _USCORECONDITION_ABATEMENT.fields_by_name['string_value']) _USCORECONDITION_ABATEMENT.fields_by_name['string_value'].containing_oneof = _USCORECONDITION_ABATEMENT.oneofs_by_name['abatement'] _USCORECONDITION_STAGE.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCORECONDITION_STAGE.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCORECONDITION_STAGE.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCORECONDITION_STAGE.fields_by_name['summary'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCORECONDITION_STAGE.fields_by_name['assessment'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORECONDITION_STAGE.containing_type = _USCORECONDITION _USCORECONDITION_EVIDENCE.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCORECONDITION_EVIDENCE.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCORECONDITION_EVIDENCE.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCORECONDITION_EVIDENCE.fields_by_name['code'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCORECONDITION_EVIDENCE.fields_by_name['detail'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORECONDITION_EVIDENCE.containing_type = _USCORECONDITION _USCORECONDITION.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._ID _USCORECONDITION.fields_by_name['meta'].message_type = proto_dot_stu3_dot_datatypes__pb2._META _USCORECONDITION.fields_by_name['implicit_rules'].message_type = proto_dot_stu3_dot_datatypes__pb2._URI _USCORECONDITION.fields_by_name['language'].message_type = proto_dot_stu3_dot_datatypes__pb2._LANGUAGECODE _USCORECONDITION.fields_by_name['text'].message_type = proto_dot_stu3_dot_metadatatypes__pb2._NARRATIVE _USCORECONDITION.fields_by_name['contained'].message_type = proto_dot_stu3_dot_resources__pb2._CONTAINEDRESOURCE _USCORECONDITION.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCORECONDITION.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCORECONDITION.fields_by_name['identifier'].message_type = proto_dot_stu3_dot_datatypes__pb2._IDENTIFIER _USCORECONDITION.fields_by_name['clinical_status'].message_type = proto_dot_stu3_dot_codes__pb2._CONDITIONCLINICALSTATUSCODESCODE _USCORECONDITION.fields_by_name['verification_status'].message_type = proto_dot_stu3_dot_codes__pb2._CONDITIONVERIFICATIONSTATUSCODE _USCORECONDITION.fields_by_name['category'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCORECONDITION.fields_by_name['severity'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCORECONDITION.fields_by_name['code'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCORECONDITION.fields_by_name['body_site'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCORECONDITION.fields_by_name['subject'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORECONDITION.fields_by_name['context'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORECONDITION.fields_by_name['onset'].message_type = _USCORECONDITION_ONSET _USCORECONDITION.fields_by_name['abatement'].message_type = _USCORECONDITION_ABATEMENT _USCORECONDITION.fields_by_name['asserted_date'].message_type = proto_dot_stu3_dot_datatypes__pb2._DATETIME _USCORECONDITION.fields_by_name['asserter'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORECONDITION.fields_by_name['stage'].message_type = _USCORECONDITION_STAGE _USCORECONDITION.fields_by_name['evidence'].message_type = _USCORECONDITION_EVIDENCE _USCORECONDITION.fields_by_name['note'].message_type = proto_dot_stu3_dot_datatypes__pb2._ANNOTATION _USCOREDEVICE_UDI.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREDEVICE_UDI.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREDEVICE_UDI.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREDEVICE_UDI.fields_by_name['device_identifier'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREDEVICE_UDI.fields_by_name['name'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREDEVICE_UDI.fields_by_name['jurisdiction'].message_type = proto_dot_stu3_dot_datatypes__pb2._URI _USCOREDEVICE_UDI.fields_by_name['carrier_h_r_f'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREDEVICE_UDI.fields_by_name['carrier_a_i_d_c'].message_type = proto_dot_stu3_dot_datatypes__pb2._BASE64BINARY _USCOREDEVICE_UDI.fields_by_name['issuer'].message_type = proto_dot_stu3_dot_datatypes__pb2._URI _USCOREDEVICE_UDI.fields_by_name['entry_type'].message_type = proto_dot_stu3_dot_codes__pb2._UDIENTRYTYPECODE _USCOREDEVICE_UDI.containing_type = _USCOREDEVICE _USCOREDEVICE.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._ID _USCOREDEVICE.fields_by_name['meta'].message_type = proto_dot_stu3_dot_datatypes__pb2._META _USCOREDEVICE.fields_by_name['implicit_rules'].message_type = proto_dot_stu3_dot_datatypes__pb2._URI _USCOREDEVICE.fields_by_name['language'].message_type = proto_dot_stu3_dot_datatypes__pb2._LANGUAGECODE _USCOREDEVICE.fields_by_name['text'].message_type = proto_dot_stu3_dot_metadatatypes__pb2._NARRATIVE _USCOREDEVICE.fields_by_name['contained'].message_type = proto_dot_stu3_dot_resources__pb2._CONTAINEDRESOURCE _USCOREDEVICE.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREDEVICE.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREDEVICE.fields_by_name['identifier'].message_type = proto_dot_stu3_dot_datatypes__pb2._IDENTIFIER _USCOREDEVICE.fields_by_name['udi'].message_type = _USCOREDEVICE_UDI _USCOREDEVICE.fields_by_name['status'].message_type = proto_dot_stu3_dot_codes__pb2._FHIRDEVICESTATUSCODE _USCOREDEVICE.fields_by_name['type'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREDEVICE.fields_by_name['lot_number'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREDEVICE.fields_by_name['manufacturer'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREDEVICE.fields_by_name['manufacture_date'].message_type = proto_dot_stu3_dot_datatypes__pb2._DATETIME _USCOREDEVICE.fields_by_name['expiration_date'].message_type = proto_dot_stu3_dot_datatypes__pb2._DATETIME _USCOREDEVICE.fields_by_name['model'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREDEVICE.fields_by_name['version'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREDEVICE.fields_by_name['patient'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREDEVICE.fields_by_name['owner'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREDEVICE.fields_by_name['contact'].message_type = proto_dot_stu3_dot_datatypes__pb2._CONTACTPOINT _USCOREDEVICE.fields_by_name['location'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREDEVICE.fields_by_name['url'].message_type = proto_dot_stu3_dot_datatypes__pb2._URI _USCOREDEVICE.fields_by_name['note'].message_type = proto_dot_stu3_dot_datatypes__pb2._ANNOTATION _USCOREDEVICE.fields_by_name['safety'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREDIAGNOSTICREPORT_EFFECTIVE.fields_by_name['date_time'].message_type = proto_dot_stu3_dot_datatypes__pb2._DATETIME _USCOREDIAGNOSTICREPORT_EFFECTIVE.fields_by_name['period'].message_type = proto_dot_stu3_dot_datatypes__pb2._PERIOD _USCOREDIAGNOSTICREPORT_EFFECTIVE.containing_type = _USCOREDIAGNOSTICREPORT _USCOREDIAGNOSTICREPORT_EFFECTIVE.oneofs_by_name['effective'].fields.append( _USCOREDIAGNOSTICREPORT_EFFECTIVE.fields_by_name['date_time']) _USCOREDIAGNOSTICREPORT_EFFECTIVE.fields_by_name['date_time'].containing_oneof = _USCOREDIAGNOSTICREPORT_EFFECTIVE.oneofs_by_name['effective'] _USCOREDIAGNOSTICREPORT_EFFECTIVE.oneofs_by_name['effective'].fields.append( _USCOREDIAGNOSTICREPORT_EFFECTIVE.fields_by_name['period']) _USCOREDIAGNOSTICREPORT_EFFECTIVE.fields_by_name['period'].containing_oneof = _USCOREDIAGNOSTICREPORT_EFFECTIVE.oneofs_by_name['effective'] _USCOREDIAGNOSTICREPORT_PERFORMER.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREDIAGNOSTICREPORT_PERFORMER.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREDIAGNOSTICREPORT_PERFORMER.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREDIAGNOSTICREPORT_PERFORMER.fields_by_name['role'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREDIAGNOSTICREPORT_PERFORMER.fields_by_name['actor'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREDIAGNOSTICREPORT_PERFORMER.containing_type = _USCOREDIAGNOSTICREPORT _USCOREDIAGNOSTICREPORT_IMAGE.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREDIAGNOSTICREPORT_IMAGE.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREDIAGNOSTICREPORT_IMAGE.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREDIAGNOSTICREPORT_IMAGE.fields_by_name['comment'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREDIAGNOSTICREPORT_IMAGE.fields_by_name['link'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREDIAGNOSTICREPORT_IMAGE.containing_type = _USCOREDIAGNOSTICREPORT _USCOREDIAGNOSTICREPORT.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._ID _USCOREDIAGNOSTICREPORT.fields_by_name['meta'].message_type = proto_dot_stu3_dot_datatypes__pb2._META _USCOREDIAGNOSTICREPORT.fields_by_name['implicit_rules'].message_type = proto_dot_stu3_dot_datatypes__pb2._URI _USCOREDIAGNOSTICREPORT.fields_by_name['language'].message_type = proto_dot_stu3_dot_datatypes__pb2._LANGUAGECODE _USCOREDIAGNOSTICREPORT.fields_by_name['text'].message_type = proto_dot_stu3_dot_metadatatypes__pb2._NARRATIVE _USCOREDIAGNOSTICREPORT.fields_by_name['contained'].message_type = proto_dot_stu3_dot_resources__pb2._CONTAINEDRESOURCE _USCOREDIAGNOSTICREPORT.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREDIAGNOSTICREPORT.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREDIAGNOSTICREPORT.fields_by_name['identifier'].message_type = proto_dot_stu3_dot_datatypes__pb2._IDENTIFIER _USCOREDIAGNOSTICREPORT.fields_by_name['based_on'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREDIAGNOSTICREPORT.fields_by_name['status'].message_type = proto_dot_stu3_dot_codes__pb2._DIAGNOSTICREPORTSTATUSCODE _USCOREDIAGNOSTICREPORT.fields_by_name['category'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREDIAGNOSTICREPORT.fields_by_name['code'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREDIAGNOSTICREPORT.fields_by_name['subject'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREDIAGNOSTICREPORT.fields_by_name['context'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREDIAGNOSTICREPORT.fields_by_name['effective'].message_type = _USCOREDIAGNOSTICREPORT_EFFECTIVE _USCOREDIAGNOSTICREPORT.fields_by_name['issued'].message_type = proto_dot_stu3_dot_datatypes__pb2._INSTANT _USCOREDIAGNOSTICREPORT.fields_by_name['performer'].message_type = _USCOREDIAGNOSTICREPORT_PERFORMER _USCOREDIAGNOSTICREPORT.fields_by_name['specimen'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREDIAGNOSTICREPORT.fields_by_name['result'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREDIAGNOSTICREPORT.fields_by_name['imaging_study'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREDIAGNOSTICREPORT.fields_by_name['image'].message_type = _USCOREDIAGNOSTICREPORT_IMAGE _USCOREDIAGNOSTICREPORT.fields_by_name['conclusion'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREDIAGNOSTICREPORT.fields_by_name['coded_diagnosis'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREDIAGNOSTICREPORT.fields_by_name['presented_form'].message_type = proto_dot_stu3_dot_datatypes__pb2._ATTACHMENT _CONTACTPOINTUSCOREDIRECT.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _CONTACTPOINTUSCOREDIRECT.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _CONTACTPOINTUSCOREDIRECT.fields_by_name['value_boolean'].message_type = proto_dot_stu3_dot_datatypes__pb2._BOOLEAN _PATIENTUSCOREETHNICITYEXTENSION.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _PATIENTUSCOREETHNICITYEXTENSION.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _PATIENTUSCOREETHNICITYEXTENSION.fields_by_name['omb_category'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODING _PATIENTUSCOREETHNICITYEXTENSION.fields_by_name['detailed'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODING _PATIENTUSCOREETHNICITYEXTENSION.fields_by_name['text'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREGOAL_START.fields_by_name['date'].message_type = proto_dot_stu3_dot_datatypes__pb2._DATE _USCOREGOAL_START.fields_by_name['codeable_concept'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREGOAL_START.containing_type = _USCOREGOAL _USCOREGOAL_START.oneofs_by_name['start'].fields.append( _USCOREGOAL_START.fields_by_name['date']) _USCOREGOAL_START.fields_by_name['date'].containing_oneof = _USCOREGOAL_START.oneofs_by_name['start'] _USCOREGOAL_START.oneofs_by_name['start'].fields.append( _USCOREGOAL_START.fields_by_name['codeable_concept']) _USCOREGOAL_START.fields_by_name['codeable_concept'].containing_oneof = _USCOREGOAL_START.oneofs_by_name['start'] _USCOREGOAL_TARGET_DETAIL.fields_by_name['quantity'].message_type = proto_dot_stu3_dot_datatypes__pb2._QUANTITY _USCOREGOAL_TARGET_DETAIL.fields_by_name['range'].message_type = proto_dot_stu3_dot_datatypes__pb2._RANGE _USCOREGOAL_TARGET_DETAIL.fields_by_name['codeable_concept'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREGOAL_TARGET_DETAIL.containing_type = _USCOREGOAL_TARGET _USCOREGOAL_TARGET_DETAIL.oneofs_by_name['detail'].fields.append( _USCOREGOAL_TARGET_DETAIL.fields_by_name['quantity']) _USCOREGOAL_TARGET_DETAIL.fields_by_name['quantity'].containing_oneof = _USCOREGOAL_TARGET_DETAIL.oneofs_by_name['detail'] _USCOREGOAL_TARGET_DETAIL.oneofs_by_name['detail'].fields.append( _USCOREGOAL_TARGET_DETAIL.fields_by_name['range']) _USCOREGOAL_TARGET_DETAIL.fields_by_name['range'].containing_oneof = _USCOREGOAL_TARGET_DETAIL.oneofs_by_name['detail'] _USCOREGOAL_TARGET_DETAIL.oneofs_by_name['detail'].fields.append( _USCOREGOAL_TARGET_DETAIL.fields_by_name['codeable_concept']) _USCOREGOAL_TARGET_DETAIL.fields_by_name['codeable_concept'].containing_oneof = _USCOREGOAL_TARGET_DETAIL.oneofs_by_name['detail'] _USCOREGOAL_TARGET_DUE.fields_by_name['date'].message_type = proto_dot_stu3_dot_datatypes__pb2._DATE _USCOREGOAL_TARGET_DUE.fields_by_name['duration'].message_type = proto_dot_stu3_dot_datatypes__pb2._DURATION _USCOREGOAL_TARGET_DUE.containing_type = _USCOREGOAL_TARGET _USCOREGOAL_TARGET_DUE.oneofs_by_name['due'].fields.append( _USCOREGOAL_TARGET_DUE.fields_by_name['date']) _USCOREGOAL_TARGET_DUE.fields_by_name['date'].containing_oneof = _USCOREGOAL_TARGET_DUE.oneofs_by_name['due'] _USCOREGOAL_TARGET_DUE.oneofs_by_name['due'].fields.append( _USCOREGOAL_TARGET_DUE.fields_by_name['duration']) _USCOREGOAL_TARGET_DUE.fields_by_name['duration'].containing_oneof = _USCOREGOAL_TARGET_DUE.oneofs_by_name['due'] _USCOREGOAL_TARGET.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREGOAL_TARGET.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREGOAL_TARGET.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREGOAL_TARGET.fields_by_name['measure'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREGOAL_TARGET.fields_by_name['detail'].message_type = _USCOREGOAL_TARGET_DETAIL _USCOREGOAL_TARGET.fields_by_name['due'].message_type = _USCOREGOAL_TARGET_DUE _USCOREGOAL_TARGET.containing_type = _USCOREGOAL _USCOREGOAL.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._ID _USCOREGOAL.fields_by_name['meta'].message_type = proto_dot_stu3_dot_datatypes__pb2._META _USCOREGOAL.fields_by_name['implicit_rules'].message_type = proto_dot_stu3_dot_datatypes__pb2._URI _USCOREGOAL.fields_by_name['language'].message_type = proto_dot_stu3_dot_datatypes__pb2._LANGUAGECODE _USCOREGOAL.fields_by_name['text'].message_type = proto_dot_stu3_dot_metadatatypes__pb2._NARRATIVE _USCOREGOAL.fields_by_name['contained'].message_type = proto_dot_stu3_dot_resources__pb2._CONTAINEDRESOURCE _USCOREGOAL.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREGOAL.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREGOAL.fields_by_name['identifier'].message_type = proto_dot_stu3_dot_datatypes__pb2._IDENTIFIER _USCOREGOAL.fields_by_name['status'].message_type = proto_dot_stu3_dot_codes__pb2._GOALSTATUSCODE _USCOREGOAL.fields_by_name['category'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREGOAL.fields_by_name['priority'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREGOAL.fields_by_name['description'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREGOAL.fields_by_name['subject'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREGOAL.fields_by_name['start'].message_type = _USCOREGOAL_START _USCOREGOAL.fields_by_name['target'].message_type = _USCOREGOAL_TARGET _USCOREGOAL.fields_by_name['status_date'].message_type = proto_dot_stu3_dot_datatypes__pb2._DATE _USCOREGOAL.fields_by_name['status_reason'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREGOAL.fields_by_name['expressed_by'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREGOAL.fields_by_name['addresses'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREGOAL.fields_by_name['note'].message_type = proto_dot_stu3_dot_datatypes__pb2._ANNOTATION _USCOREGOAL.fields_by_name['outcome_code'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREGOAL.fields_by_name['outcome_reference'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREIMMUNIZATION_PRACTITIONER.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREIMMUNIZATION_PRACTITIONER.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREIMMUNIZATION_PRACTITIONER.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREIMMUNIZATION_PRACTITIONER.fields_by_name['role'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREIMMUNIZATION_PRACTITIONER.fields_by_name['actor'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREIMMUNIZATION_PRACTITIONER.containing_type = _USCOREIMMUNIZATION _USCOREIMMUNIZATION_EXPLANATION.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREIMMUNIZATION_EXPLANATION.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREIMMUNIZATION_EXPLANATION.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREIMMUNIZATION_EXPLANATION.fields_by_name['reason'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREIMMUNIZATION_EXPLANATION.fields_by_name['reason_not_given'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREIMMUNIZATION_EXPLANATION.containing_type = _USCOREIMMUNIZATION _USCOREIMMUNIZATION_REACTION.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREIMMUNIZATION_REACTION.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREIMMUNIZATION_REACTION.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREIMMUNIZATION_REACTION.fields_by_name['date'].message_type = proto_dot_stu3_dot_datatypes__pb2._DATETIME _USCOREIMMUNIZATION_REACTION.fields_by_name['detail'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREIMMUNIZATION_REACTION.fields_by_name['reported'].message_type = proto_dot_stu3_dot_datatypes__pb2._BOOLEAN _USCOREIMMUNIZATION_REACTION.containing_type = _USCOREIMMUNIZATION _USCOREIMMUNIZATION_VACCINATIONPROTOCOL.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREIMMUNIZATION_VACCINATIONPROTOCOL.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREIMMUNIZATION_VACCINATIONPROTOCOL.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREIMMUNIZATION_VACCINATIONPROTOCOL.fields_by_name['dose_sequence'].message_type = proto_dot_stu3_dot_datatypes__pb2._POSITIVEINT _USCOREIMMUNIZATION_VACCINATIONPROTOCOL.fields_by_name['description'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREIMMUNIZATION_VACCINATIONPROTOCOL.fields_by_name['authority'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREIMMUNIZATION_VACCINATIONPROTOCOL.fields_by_name['series'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREIMMUNIZATION_VACCINATIONPROTOCOL.fields_by_name['series_doses'].message_type = proto_dot_stu3_dot_datatypes__pb2._POSITIVEINT _USCOREIMMUNIZATION_VACCINATIONPROTOCOL.fields_by_name['target_disease'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREIMMUNIZATION_VACCINATIONPROTOCOL.fields_by_name['dose_status'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREIMMUNIZATION_VACCINATIONPROTOCOL.fields_by_name['dose_status_reason'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREIMMUNIZATION_VACCINATIONPROTOCOL.containing_type = _USCOREIMMUNIZATION _USCOREIMMUNIZATION.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._ID _USCOREIMMUNIZATION.fields_by_name['meta'].message_type = proto_dot_stu3_dot_datatypes__pb2._META _USCOREIMMUNIZATION.fields_by_name['implicit_rules'].message_type = proto_dot_stu3_dot_datatypes__pb2._URI _USCOREIMMUNIZATION.fields_by_name['language'].message_type = proto_dot_stu3_dot_datatypes__pb2._LANGUAGECODE _USCOREIMMUNIZATION.fields_by_name['text'].message_type = proto_dot_stu3_dot_metadatatypes__pb2._NARRATIVE _USCOREIMMUNIZATION.fields_by_name['contained'].message_type = proto_dot_stu3_dot_resources__pb2._CONTAINEDRESOURCE _USCOREIMMUNIZATION.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREIMMUNIZATION.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREIMMUNIZATION.fields_by_name['identifier'].message_type = proto_dot_stu3_dot_datatypes__pb2._IDENTIFIER _USCOREIMMUNIZATION.fields_by_name['status'].message_type = proto_dot_stu3_dot_codes__pb2._IMMUNIZATIONSTATUSCODESCODE _USCOREIMMUNIZATION.fields_by_name['not_given'].message_type = proto_dot_stu3_dot_datatypes__pb2._BOOLEAN _USCOREIMMUNIZATION.fields_by_name['vaccine_code'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREIMMUNIZATION.fields_by_name['patient'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREIMMUNIZATION.fields_by_name['encounter'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREIMMUNIZATION.fields_by_name['date'].message_type = proto_dot_stu3_dot_datatypes__pb2._DATETIME _USCOREIMMUNIZATION.fields_by_name['primary_source'].message_type = proto_dot_stu3_dot_datatypes__pb2._BOOLEAN _USCOREIMMUNIZATION.fields_by_name['report_origin'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREIMMUNIZATION.fields_by_name['location'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREIMMUNIZATION.fields_by_name['manufacturer'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREIMMUNIZATION.fields_by_name['lot_number'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREIMMUNIZATION.fields_by_name['expiration_date'].message_type = proto_dot_stu3_dot_datatypes__pb2._DATE _USCOREIMMUNIZATION.fields_by_name['site'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREIMMUNIZATION.fields_by_name['route'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREIMMUNIZATION.fields_by_name['dose_quantity'].message_type = proto_dot_stu3_dot_datatypes__pb2._SIMPLEQUANTITY _USCOREIMMUNIZATION.fields_by_name['practitioner'].message_type = _USCOREIMMUNIZATION_PRACTITIONER _USCOREIMMUNIZATION.fields_by_name['note'].message_type = proto_dot_stu3_dot_datatypes__pb2._ANNOTATION _USCOREIMMUNIZATION.fields_by_name['explanation'].message_type = _USCOREIMMUNIZATION_EXPLANATION _USCOREIMMUNIZATION.fields_by_name['reaction'].message_type = _USCOREIMMUNIZATION_REACTION _USCOREIMMUNIZATION.fields_by_name['vaccination_protocol'].message_type = _USCOREIMMUNIZATION_VACCINATIONPROTOCOL _USCORELOCATION_POSITION.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCORELOCATION_POSITION.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCORELOCATION_POSITION.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCORELOCATION_POSITION.fields_by_name['longitude'].message_type = proto_dot_stu3_dot_datatypes__pb2._DECIMAL _USCORELOCATION_POSITION.fields_by_name['latitude'].message_type = proto_dot_stu3_dot_datatypes__pb2._DECIMAL _USCORELOCATION_POSITION.fields_by_name['altitude'].message_type = proto_dot_stu3_dot_datatypes__pb2._DECIMAL _USCORELOCATION_POSITION.containing_type = _USCORELOCATION _USCORELOCATION.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._ID _USCORELOCATION.fields_by_name['meta'].message_type = proto_dot_stu3_dot_datatypes__pb2._META _USCORELOCATION.fields_by_name['implicit_rules'].message_type = proto_dot_stu3_dot_datatypes__pb2._URI _USCORELOCATION.fields_by_name['language'].message_type = proto_dot_stu3_dot_datatypes__pb2._LANGUAGECODE _USCORELOCATION.fields_by_name['text'].message_type = proto_dot_stu3_dot_metadatatypes__pb2._NARRATIVE _USCORELOCATION.fields_by_name['contained'].message_type = proto_dot_stu3_dot_resources__pb2._CONTAINEDRESOURCE _USCORELOCATION.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCORELOCATION.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCORELOCATION.fields_by_name['identifier'].message_type = proto_dot_stu3_dot_datatypes__pb2._IDENTIFIER _USCORELOCATION.fields_by_name['status'].message_type = proto_dot_stu3_dot_codes__pb2._LOCATIONSTATUSCODE _USCORELOCATION.fields_by_name['operational_status'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODING _USCORELOCATION.fields_by_name['name'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCORELOCATION.fields_by_name['alias'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCORELOCATION.fields_by_name['description'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCORELOCATION.fields_by_name['mode'].message_type = proto_dot_stu3_dot_codes__pb2._LOCATIONMODECODE _USCORELOCATION.fields_by_name['type'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCORELOCATION.fields_by_name['telecom'].message_type = proto_dot_stu3_dot_datatypes__pb2._CONTACTPOINT _USCORELOCATION.fields_by_name['address'].message_type = proto_dot_stu3_dot_datatypes__pb2._ADDRESS _USCORELOCATION.fields_by_name['physical_type'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCORELOCATION.fields_by_name['position'].message_type = _USCORELOCATION_POSITION _USCORELOCATION.fields_by_name['managing_organization'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORELOCATION.fields_by_name['part_of'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORELOCATION.fields_by_name['endpoint'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREMEDICATION_INGREDIENT_ITEM.fields_by_name['codeable_concept'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREMEDICATION_INGREDIENT_ITEM.fields_by_name['reference'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREMEDICATION_INGREDIENT_ITEM.containing_type = _USCOREMEDICATION_INGREDIENT _USCOREMEDICATION_INGREDIENT_ITEM.oneofs_by_name['item'].fields.append( _USCOREMEDICATION_INGREDIENT_ITEM.fields_by_name['codeable_concept']) _USCOREMEDICATION_INGREDIENT_ITEM.fields_by_name['codeable_concept'].containing_oneof = _USCOREMEDICATION_INGREDIENT_ITEM.oneofs_by_name['item'] _USCOREMEDICATION_INGREDIENT_ITEM.oneofs_by_name['item'].fields.append( _USCOREMEDICATION_INGREDIENT_ITEM.fields_by_name['reference']) _USCOREMEDICATION_INGREDIENT_ITEM.fields_by_name['reference'].containing_oneof = _USCOREMEDICATION_INGREDIENT_ITEM.oneofs_by_name['item'] _USCOREMEDICATION_INGREDIENT.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREMEDICATION_INGREDIENT.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREMEDICATION_INGREDIENT.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREMEDICATION_INGREDIENT.fields_by_name['item'].message_type = _USCOREMEDICATION_INGREDIENT_ITEM _USCOREMEDICATION_INGREDIENT.fields_by_name['is_active'].message_type = proto_dot_stu3_dot_datatypes__pb2._BOOLEAN _USCOREMEDICATION_INGREDIENT.fields_by_name['amount'].message_type = proto_dot_stu3_dot_datatypes__pb2._RATIO _USCOREMEDICATION_INGREDIENT.containing_type = _USCOREMEDICATION _USCOREMEDICATION_PACKAGE_CONTENT_ITEM.fields_by_name['codeable_concept'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREMEDICATION_PACKAGE_CONTENT_ITEM.fields_by_name['reference'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREMEDICATION_PACKAGE_CONTENT_ITEM.containing_type = _USCOREMEDICATION_PACKAGE_CONTENT _USCOREMEDICATION_PACKAGE_CONTENT_ITEM.oneofs_by_name['item'].fields.append( _USCOREMEDICATION_PACKAGE_CONTENT_ITEM.fields_by_name['codeable_concept']) _USCOREMEDICATION_PACKAGE_CONTENT_ITEM.fields_by_name['codeable_concept'].containing_oneof = _USCOREMEDICATION_PACKAGE_CONTENT_ITEM.oneofs_by_name['item'] _USCOREMEDICATION_PACKAGE_CONTENT_ITEM.oneofs_by_name['item'].fields.append( _USCOREMEDICATION_PACKAGE_CONTENT_ITEM.fields_by_name['reference']) _USCOREMEDICATION_PACKAGE_CONTENT_ITEM.fields_by_name['reference'].containing_oneof = _USCOREMEDICATION_PACKAGE_CONTENT_ITEM.oneofs_by_name['item'] _USCOREMEDICATION_PACKAGE_CONTENT.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREMEDICATION_PACKAGE_CONTENT.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREMEDICATION_PACKAGE_CONTENT.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREMEDICATION_PACKAGE_CONTENT.fields_by_name['item'].message_type = _USCOREMEDICATION_PACKAGE_CONTENT_ITEM _USCOREMEDICATION_PACKAGE_CONTENT.fields_by_name['amount'].message_type = proto_dot_stu3_dot_datatypes__pb2._SIMPLEQUANTITY _USCOREMEDICATION_PACKAGE_CONTENT.containing_type = _USCOREMEDICATION_PACKAGE _USCOREMEDICATION_PACKAGE_BATCH.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREMEDICATION_PACKAGE_BATCH.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREMEDICATION_PACKAGE_BATCH.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREMEDICATION_PACKAGE_BATCH.fields_by_name['lot_number'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREMEDICATION_PACKAGE_BATCH.fields_by_name['expiration_date'].message_type = proto_dot_stu3_dot_datatypes__pb2._DATETIME _USCOREMEDICATION_PACKAGE_BATCH.containing_type = _USCOREMEDICATION_PACKAGE _USCOREMEDICATION_PACKAGE.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREMEDICATION_PACKAGE.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREMEDICATION_PACKAGE.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREMEDICATION_PACKAGE.fields_by_name['container'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREMEDICATION_PACKAGE.fields_by_name['content'].message_type = _USCOREMEDICATION_PACKAGE_CONTENT _USCOREMEDICATION_PACKAGE.fields_by_name['batch'].message_type = _USCOREMEDICATION_PACKAGE_BATCH _USCOREMEDICATION_PACKAGE.containing_type = _USCOREMEDICATION _USCOREMEDICATION.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._ID _USCOREMEDICATION.fields_by_name['meta'].message_type = proto_dot_stu3_dot_datatypes__pb2._META _USCOREMEDICATION.fields_by_name['implicit_rules'].message_type = proto_dot_stu3_dot_datatypes__pb2._URI _USCOREMEDICATION.fields_by_name['language'].message_type = proto_dot_stu3_dot_datatypes__pb2._LANGUAGECODE _USCOREMEDICATION.fields_by_name['text'].message_type = proto_dot_stu3_dot_metadatatypes__pb2._NARRATIVE _USCOREMEDICATION.fields_by_name['contained'].message_type = proto_dot_stu3_dot_resources__pb2._CONTAINEDRESOURCE _USCOREMEDICATION.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREMEDICATION.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREMEDICATION.fields_by_name['code'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREMEDICATION.fields_by_name['status'].message_type = proto_dot_stu3_dot_codes__pb2._MEDICATIONSTATUSCODE _USCOREMEDICATION.fields_by_name['is_brand'].message_type = proto_dot_stu3_dot_datatypes__pb2._BOOLEAN _USCOREMEDICATION.fields_by_name['is_over_the_counter'].message_type = proto_dot_stu3_dot_datatypes__pb2._BOOLEAN _USCOREMEDICATION.fields_by_name['manufacturer'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREMEDICATION.fields_by_name['form'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREMEDICATION.fields_by_name['ingredient'].message_type = _USCOREMEDICATION_INGREDIENT _USCOREMEDICATION.fields_by_name['package_value'].message_type = _USCOREMEDICATION_PACKAGE _USCOREMEDICATION.fields_by_name['image'].message_type = proto_dot_stu3_dot_datatypes__pb2._ATTACHMENT _USCOREMEDICATIONREQUEST_MEDICATION.fields_by_name['codeable_concept'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREMEDICATIONREQUEST_MEDICATION.fields_by_name['reference'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREMEDICATIONREQUEST_MEDICATION.containing_type = _USCOREMEDICATIONREQUEST _USCOREMEDICATIONREQUEST_MEDICATION.oneofs_by_name['medication'].fields.append( _USCOREMEDICATIONREQUEST_MEDICATION.fields_by_name['codeable_concept']) _USCOREMEDICATIONREQUEST_MEDICATION.fields_by_name['codeable_concept'].containing_oneof = _USCOREMEDICATIONREQUEST_MEDICATION.oneofs_by_name['medication'] _USCOREMEDICATIONREQUEST_MEDICATION.oneofs_by_name['medication'].fields.append( _USCOREMEDICATIONREQUEST_MEDICATION.fields_by_name['reference']) _USCOREMEDICATIONREQUEST_MEDICATION.fields_by_name['reference'].containing_oneof = _USCOREMEDICATIONREQUEST_MEDICATION.oneofs_by_name['medication'] _USCOREMEDICATIONREQUEST_REQUESTER.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREMEDICATIONREQUEST_REQUESTER.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREMEDICATIONREQUEST_REQUESTER.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREMEDICATIONREQUEST_REQUESTER.fields_by_name['agent'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREMEDICATIONREQUEST_REQUESTER.fields_by_name['on_behalf_of'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREMEDICATIONREQUEST_REQUESTER.containing_type = _USCOREMEDICATIONREQUEST _USCOREMEDICATIONREQUEST_DISPENSEREQUEST.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREMEDICATIONREQUEST_DISPENSEREQUEST.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREMEDICATIONREQUEST_DISPENSEREQUEST.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREMEDICATIONREQUEST_DISPENSEREQUEST.fields_by_name['validity_period'].message_type = proto_dot_stu3_dot_datatypes__pb2._PERIOD _USCOREMEDICATIONREQUEST_DISPENSEREQUEST.fields_by_name['number_of_repeats_allowed'].message_type = proto_dot_stu3_dot_datatypes__pb2._POSITIVEINT _USCOREMEDICATIONREQUEST_DISPENSEREQUEST.fields_by_name['quantity'].message_type = proto_dot_stu3_dot_datatypes__pb2._SIMPLEQUANTITY _USCOREMEDICATIONREQUEST_DISPENSEREQUEST.fields_by_name['expected_supply_duration'].message_type = proto_dot_stu3_dot_datatypes__pb2._DURATION _USCOREMEDICATIONREQUEST_DISPENSEREQUEST.fields_by_name['performer'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREMEDICATIONREQUEST_DISPENSEREQUEST.containing_type = _USCOREMEDICATIONREQUEST _USCOREMEDICATIONREQUEST_SUBSTITUTION.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREMEDICATIONREQUEST_SUBSTITUTION.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREMEDICATIONREQUEST_SUBSTITUTION.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREMEDICATIONREQUEST_SUBSTITUTION.fields_by_name['allowed'].message_type = proto_dot_stu3_dot_datatypes__pb2._BOOLEAN _USCOREMEDICATIONREQUEST_SUBSTITUTION.fields_by_name['reason'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREMEDICATIONREQUEST_SUBSTITUTION.containing_type = _USCOREMEDICATIONREQUEST _USCOREMEDICATIONREQUEST.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._ID _USCOREMEDICATIONREQUEST.fields_by_name['meta'].message_type = proto_dot_stu3_dot_datatypes__pb2._META _USCOREMEDICATIONREQUEST.fields_by_name['implicit_rules'].message_type = proto_dot_stu3_dot_datatypes__pb2._URI _USCOREMEDICATIONREQUEST.fields_by_name['language'].message_type = proto_dot_stu3_dot_datatypes__pb2._LANGUAGECODE _USCOREMEDICATIONREQUEST.fields_by_name['text'].message_type = proto_dot_stu3_dot_metadatatypes__pb2._NARRATIVE _USCOREMEDICATIONREQUEST.fields_by_name['contained'].message_type = proto_dot_stu3_dot_resources__pb2._CONTAINEDRESOURCE _USCOREMEDICATIONREQUEST.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREMEDICATIONREQUEST.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREMEDICATIONREQUEST.fields_by_name['identifier'].message_type = proto_dot_stu3_dot_datatypes__pb2._IDENTIFIER _USCOREMEDICATIONREQUEST.fields_by_name['definition'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREMEDICATIONREQUEST.fields_by_name['based_on'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREMEDICATIONREQUEST.fields_by_name['group_identifier'].message_type = proto_dot_stu3_dot_datatypes__pb2._IDENTIFIER _USCOREMEDICATIONREQUEST.fields_by_name['status'].message_type = proto_dot_stu3_dot_codes__pb2._MEDICATIONREQUESTSTATUSCODE _USCOREMEDICATIONREQUEST.fields_by_name['intent'].message_type = proto_dot_stu3_dot_codes__pb2._MEDICATIONREQUESTINTENTCODE _USCOREMEDICATIONREQUEST.fields_by_name['category'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREMEDICATIONREQUEST.fields_by_name['priority'].message_type = proto_dot_stu3_dot_codes__pb2._MEDICATIONREQUESTPRIORITYCODE _USCOREMEDICATIONREQUEST.fields_by_name['medication'].message_type = _USCOREMEDICATIONREQUEST_MEDICATION _USCOREMEDICATIONREQUEST.fields_by_name['subject'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREMEDICATIONREQUEST.fields_by_name['context'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREMEDICATIONREQUEST.fields_by_name['supporting_information'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREMEDICATIONREQUEST.fields_by_name['authored_on'].message_type = proto_dot_stu3_dot_datatypes__pb2._DATETIME _USCOREMEDICATIONREQUEST.fields_by_name['requester'].message_type = _USCOREMEDICATIONREQUEST_REQUESTER _USCOREMEDICATIONREQUEST.fields_by_name['recorder'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREMEDICATIONREQUEST.fields_by_name['reason_code'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREMEDICATIONREQUEST.fields_by_name['reason_reference'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREMEDICATIONREQUEST.fields_by_name['note'].message_type = proto_dot_stu3_dot_datatypes__pb2._ANNOTATION _USCOREMEDICATIONREQUEST.fields_by_name['dosage_instruction'].message_type = proto_dot_stu3_dot_datatypes__pb2._DOSAGE _USCOREMEDICATIONREQUEST.fields_by_name['dispense_request'].message_type = _USCOREMEDICATIONREQUEST_DISPENSEREQUEST _USCOREMEDICATIONREQUEST.fields_by_name['substitution'].message_type = _USCOREMEDICATIONREQUEST_SUBSTITUTION _USCOREMEDICATIONREQUEST.fields_by_name['prior_prescription'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREMEDICATIONREQUEST.fields_by_name['detected_issue'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREMEDICATIONREQUEST.fields_by_name['event_history'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREMEDICATIONSTATEMENT_MEDICATION.fields_by_name['codeable_concept'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREMEDICATIONSTATEMENT_MEDICATION.fields_by_name['reference'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREMEDICATIONSTATEMENT_MEDICATION.containing_type = _USCOREMEDICATIONSTATEMENT _USCOREMEDICATIONSTATEMENT_MEDICATION.oneofs_by_name['medication'].fields.append( _USCOREMEDICATIONSTATEMENT_MEDICATION.fields_by_name['codeable_concept']) _USCOREMEDICATIONSTATEMENT_MEDICATION.fields_by_name['codeable_concept'].containing_oneof = _USCOREMEDICATIONSTATEMENT_MEDICATION.oneofs_by_name['medication'] _USCOREMEDICATIONSTATEMENT_MEDICATION.oneofs_by_name['medication'].fields.append( _USCOREMEDICATIONSTATEMENT_MEDICATION.fields_by_name['reference']) _USCOREMEDICATIONSTATEMENT_MEDICATION.fields_by_name['reference'].containing_oneof = _USCOREMEDICATIONSTATEMENT_MEDICATION.oneofs_by_name['medication'] _USCOREMEDICATIONSTATEMENT_EFFECTIVE.fields_by_name['date_time'].message_type = proto_dot_stu3_dot_datatypes__pb2._DATETIME _USCOREMEDICATIONSTATEMENT_EFFECTIVE.fields_by_name['period'].message_type = proto_dot_stu3_dot_datatypes__pb2._PERIOD _USCOREMEDICATIONSTATEMENT_EFFECTIVE.containing_type = _USCOREMEDICATIONSTATEMENT _USCOREMEDICATIONSTATEMENT_EFFECTIVE.oneofs_by_name['effective'].fields.append( _USCOREMEDICATIONSTATEMENT_EFFECTIVE.fields_by_name['date_time']) _USCOREMEDICATIONSTATEMENT_EFFECTIVE.fields_by_name['date_time'].containing_oneof = _USCOREMEDICATIONSTATEMENT_EFFECTIVE.oneofs_by_name['effective'] _USCOREMEDICATIONSTATEMENT_EFFECTIVE.oneofs_by_name['effective'].fields.append( _USCOREMEDICATIONSTATEMENT_EFFECTIVE.fields_by_name['period']) _USCOREMEDICATIONSTATEMENT_EFFECTIVE.fields_by_name['period'].containing_oneof = _USCOREMEDICATIONSTATEMENT_EFFECTIVE.oneofs_by_name['effective'] _USCOREMEDICATIONSTATEMENT.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._ID _USCOREMEDICATIONSTATEMENT.fields_by_name['meta'].message_type = proto_dot_stu3_dot_datatypes__pb2._META _USCOREMEDICATIONSTATEMENT.fields_by_name['implicit_rules'].message_type = proto_dot_stu3_dot_datatypes__pb2._URI _USCOREMEDICATIONSTATEMENT.fields_by_name['language'].message_type = proto_dot_stu3_dot_datatypes__pb2._LANGUAGECODE _USCOREMEDICATIONSTATEMENT.fields_by_name['text'].message_type = proto_dot_stu3_dot_metadatatypes__pb2._NARRATIVE _USCOREMEDICATIONSTATEMENT.fields_by_name['contained'].message_type = proto_dot_stu3_dot_resources__pb2._CONTAINEDRESOURCE _USCOREMEDICATIONSTATEMENT.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREMEDICATIONSTATEMENT.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREMEDICATIONSTATEMENT.fields_by_name['identifier'].message_type = proto_dot_stu3_dot_datatypes__pb2._IDENTIFIER _USCOREMEDICATIONSTATEMENT.fields_by_name['based_on'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREMEDICATIONSTATEMENT.fields_by_name['part_of'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREMEDICATIONSTATEMENT.fields_by_name['context'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREMEDICATIONSTATEMENT.fields_by_name['status'].message_type = proto_dot_stu3_dot_codes__pb2._MEDICATIONSTATEMENTSTATUSCODE _USCOREMEDICATIONSTATEMENT.fields_by_name['category'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREMEDICATIONSTATEMENT.fields_by_name['medication'].message_type = _USCOREMEDICATIONSTATEMENT_MEDICATION _USCOREMEDICATIONSTATEMENT.fields_by_name['effective'].message_type = _USCOREMEDICATIONSTATEMENT_EFFECTIVE _USCOREMEDICATIONSTATEMENT.fields_by_name['date_asserted'].message_type = proto_dot_stu3_dot_datatypes__pb2._DATETIME _USCOREMEDICATIONSTATEMENT.fields_by_name['information_source'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREMEDICATIONSTATEMENT.fields_by_name['subject'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREMEDICATIONSTATEMENT.fields_by_name['derived_from'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREMEDICATIONSTATEMENT.fields_by_name['taken'].message_type = proto_dot_stu3_dot_codes__pb2._MEDICATIONSTATEMENTTAKENCODE _USCOREMEDICATIONSTATEMENT.fields_by_name['reason_not_taken'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREMEDICATIONSTATEMENT.fields_by_name['reason_code'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREMEDICATIONSTATEMENT.fields_by_name['reason_reference'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREMEDICATIONSTATEMENT.fields_by_name['note'].message_type = proto_dot_stu3_dot_datatypes__pb2._ANNOTATION _USCOREMEDICATIONSTATEMENT.fields_by_name['dosage'].message_type = proto_dot_stu3_dot_datatypes__pb2._DOSAGE _USCOREOBSERVATIONRESULTS_EFFECTIVE.fields_by_name['date_time'].message_type = proto_dot_stu3_dot_datatypes__pb2._DATETIME _USCOREOBSERVATIONRESULTS_EFFECTIVE.fields_by_name['period'].message_type = proto_dot_stu3_dot_datatypes__pb2._PERIOD _USCOREOBSERVATIONRESULTS_EFFECTIVE.containing_type = _USCOREOBSERVATIONRESULTS _USCOREOBSERVATIONRESULTS_EFFECTIVE.oneofs_by_name['effective'].fields.append( _USCOREOBSERVATIONRESULTS_EFFECTIVE.fields_by_name['date_time']) _USCOREOBSERVATIONRESULTS_EFFECTIVE.fields_by_name['date_time'].containing_oneof = _USCOREOBSERVATIONRESULTS_EFFECTIVE.oneofs_by_name['effective'] _USCOREOBSERVATIONRESULTS_EFFECTIVE.oneofs_by_name['effective'].fields.append( _USCOREOBSERVATIONRESULTS_EFFECTIVE.fields_by_name['period']) _USCOREOBSERVATIONRESULTS_EFFECTIVE.fields_by_name['period'].containing_oneof = _USCOREOBSERVATIONRESULTS_EFFECTIVE.oneofs_by_name['effective'] _USCOREOBSERVATIONRESULTS_VALUE.fields_by_name['quantity'].message_type = proto_dot_stu3_dot_datatypes__pb2._QUANTITY _USCOREOBSERVATIONRESULTS_VALUE.fields_by_name['codeable_concept'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREOBSERVATIONRESULTS_VALUE.fields_by_name['string_value'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREOBSERVATIONRESULTS_VALUE.fields_by_name['boolean'].message_type = proto_dot_stu3_dot_datatypes__pb2._BOOLEAN _USCOREOBSERVATIONRESULTS_VALUE.fields_by_name['range'].message_type = proto_dot_stu3_dot_datatypes__pb2._RANGE _USCOREOBSERVATIONRESULTS_VALUE.fields_by_name['ratio'].message_type = proto_dot_stu3_dot_datatypes__pb2._RATIO _USCOREOBSERVATIONRESULTS_VALUE.fields_by_name['sampled_data'].message_type = proto_dot_stu3_dot_datatypes__pb2._SAMPLEDDATA _USCOREOBSERVATIONRESULTS_VALUE.fields_by_name['attachment'].message_type = proto_dot_stu3_dot_datatypes__pb2._ATTACHMENT _USCOREOBSERVATIONRESULTS_VALUE.fields_by_name['time'].message_type = proto_dot_stu3_dot_datatypes__pb2._TIME _USCOREOBSERVATIONRESULTS_VALUE.fields_by_name['date_time'].message_type = proto_dot_stu3_dot_datatypes__pb2._DATETIME _USCOREOBSERVATIONRESULTS_VALUE.fields_by_name['period'].message_type = proto_dot_stu3_dot_datatypes__pb2._PERIOD _USCOREOBSERVATIONRESULTS_VALUE.containing_type = _USCOREOBSERVATIONRESULTS _USCOREOBSERVATIONRESULTS_VALUE.oneofs_by_name['value'].fields.append( _USCOREOBSERVATIONRESULTS_VALUE.fields_by_name['quantity']) _USCOREOBSERVATIONRESULTS_VALUE.fields_by_name['quantity'].containing_oneof = _USCOREOBSERVATIONRESULTS_VALUE.oneofs_by_name['value'] _USCOREOBSERVATIONRESULTS_VALUE.oneofs_by_name['value'].fields.append( _USCOREOBSERVATIONRESULTS_VALUE.fields_by_name['codeable_concept']) _USCOREOBSERVATIONRESULTS_VALUE.fields_by_name['codeable_concept'].containing_oneof = _USCOREOBSERVATIONRESULTS_VALUE.oneofs_by_name['value'] _USCOREOBSERVATIONRESULTS_VALUE.oneofs_by_name['value'].fields.append( _USCOREOBSERVATIONRESULTS_VALUE.fields_by_name['string_value']) _USCOREOBSERVATIONRESULTS_VALUE.fields_by_name['string_value'].containing_oneof = 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proto_dot_stu3_dot_datatypes__pb2._IDENTIFIER _USCOREOBSERVATIONRESULTS.fields_by_name['based_on'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREOBSERVATIONRESULTS.fields_by_name['status'].message_type = proto_dot_stu3_dot_codes__pb2._OBSERVATIONSTATUSCODE _USCOREOBSERVATIONRESULTS.fields_by_name['category'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREOBSERVATIONRESULTS.fields_by_name['code'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREOBSERVATIONRESULTS.fields_by_name['subject'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREOBSERVATIONRESULTS.fields_by_name['context'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREOBSERVATIONRESULTS.fields_by_name['effective'].message_type = _USCOREOBSERVATIONRESULTS_EFFECTIVE _USCOREOBSERVATIONRESULTS.fields_by_name['issued'].message_type = proto_dot_stu3_dot_datatypes__pb2._INSTANT _USCOREOBSERVATIONRESULTS.fields_by_name['performer'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREOBSERVATIONRESULTS.fields_by_name['value'].message_type = _USCOREOBSERVATIONRESULTS_VALUE _USCOREOBSERVATIONRESULTS.fields_by_name['data_absent_reason'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREOBSERVATIONRESULTS.fields_by_name['interpretation'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREOBSERVATIONRESULTS.fields_by_name['comment'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREOBSERVATIONRESULTS.fields_by_name['body_site'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREOBSERVATIONRESULTS.fields_by_name['method'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREOBSERVATIONRESULTS.fields_by_name['specimen'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREOBSERVATIONRESULTS.fields_by_name['device'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREOBSERVATIONRESULTS.fields_by_name['reference_range'].message_type = _USCOREOBSERVATIONRESULTS_REFERENCERANGE _USCOREOBSERVATIONRESULTS.fields_by_name['related'].message_type = _USCOREOBSERVATIONRESULTS_RELATED _USCOREOBSERVATIONRESULTS.fields_by_name['component'].message_type = _USCOREOBSERVATIONRESULTS_COMPONENT _USCOREORGANIZATION_CONTACT.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREORGANIZATION_CONTACT.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREORGANIZATION_CONTACT.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREORGANIZATION_CONTACT.fields_by_name['purpose'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREORGANIZATION_CONTACT.fields_by_name['name'].message_type = proto_dot_stu3_dot_datatypes__pb2._HUMANNAME _USCOREORGANIZATION_CONTACT.fields_by_name['telecom'].message_type = proto_dot_stu3_dot_datatypes__pb2._CONTACTPOINT _USCOREORGANIZATION_CONTACT.fields_by_name['address'].message_type = proto_dot_stu3_dot_datatypes__pb2._ADDRESS _USCOREORGANIZATION_CONTACT.containing_type = _USCOREORGANIZATION _USCOREORGANIZATION.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._ID _USCOREORGANIZATION.fields_by_name['meta'].message_type = proto_dot_stu3_dot_datatypes__pb2._META _USCOREORGANIZATION.fields_by_name['implicit_rules'].message_type = proto_dot_stu3_dot_datatypes__pb2._URI _USCOREORGANIZATION.fields_by_name['language'].message_type = proto_dot_stu3_dot_datatypes__pb2._LANGUAGECODE _USCOREORGANIZATION.fields_by_name['text'].message_type = proto_dot_stu3_dot_metadatatypes__pb2._NARRATIVE _USCOREORGANIZATION.fields_by_name['contained'].message_type = proto_dot_stu3_dot_resources__pb2._CONTAINEDRESOURCE _USCOREORGANIZATION.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREORGANIZATION.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREORGANIZATION.fields_by_name['identifier'].message_type = proto_dot_stu3_dot_datatypes__pb2._IDENTIFIER _USCOREORGANIZATION.fields_by_name['active'].message_type = proto_dot_stu3_dot_datatypes__pb2._BOOLEAN _USCOREORGANIZATION.fields_by_name['type'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREORGANIZATION.fields_by_name['name'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREORGANIZATION.fields_by_name['alias'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREORGANIZATION.fields_by_name['telecom'].message_type = proto_dot_stu3_dot_datatypes__pb2._CONTACTPOINT _USCOREORGANIZATION.fields_by_name['address'].message_type = proto_dot_stu3_dot_datatypes__pb2._ADDRESS _USCOREORGANIZATION.fields_by_name['part_of'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREORGANIZATION.fields_by_name['contact'].message_type = _USCOREORGANIZATION_CONTACT _USCOREORGANIZATION.fields_by_name['endpoint'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREPATIENT_DECEASED.fields_by_name['boolean'].message_type = proto_dot_stu3_dot_datatypes__pb2._BOOLEAN _USCOREPATIENT_DECEASED.fields_by_name['date_time'].message_type = proto_dot_stu3_dot_datatypes__pb2._DATETIME _USCOREPATIENT_DECEASED.containing_type = _USCOREPATIENT _USCOREPATIENT_DECEASED.oneofs_by_name['deceased'].fields.append( _USCOREPATIENT_DECEASED.fields_by_name['boolean']) _USCOREPATIENT_DECEASED.fields_by_name['boolean'].containing_oneof = _USCOREPATIENT_DECEASED.oneofs_by_name['deceased'] _USCOREPATIENT_DECEASED.oneofs_by_name['deceased'].fields.append( _USCOREPATIENT_DECEASED.fields_by_name['date_time']) _USCOREPATIENT_DECEASED.fields_by_name['date_time'].containing_oneof = _USCOREPATIENT_DECEASED.oneofs_by_name['deceased'] _USCOREPATIENT_MULTIPLEBIRTH.fields_by_name['boolean'].message_type = proto_dot_stu3_dot_datatypes__pb2._BOOLEAN _USCOREPATIENT_MULTIPLEBIRTH.fields_by_name['integer'].message_type = proto_dot_stu3_dot_datatypes__pb2._INTEGER _USCOREPATIENT_MULTIPLEBIRTH.containing_type = _USCOREPATIENT _USCOREPATIENT_MULTIPLEBIRTH.oneofs_by_name['multiple_birth'].fields.append( _USCOREPATIENT_MULTIPLEBIRTH.fields_by_name['boolean']) _USCOREPATIENT_MULTIPLEBIRTH.fields_by_name['boolean'].containing_oneof = _USCOREPATIENT_MULTIPLEBIRTH.oneofs_by_name['multiple_birth'] _USCOREPATIENT_MULTIPLEBIRTH.oneofs_by_name['multiple_birth'].fields.append( _USCOREPATIENT_MULTIPLEBIRTH.fields_by_name['integer']) _USCOREPATIENT_MULTIPLEBIRTH.fields_by_name['integer'].containing_oneof = _USCOREPATIENT_MULTIPLEBIRTH.oneofs_by_name['multiple_birth'] _USCOREPATIENT_CONTACT.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREPATIENT_CONTACT.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREPATIENT_CONTACT.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREPATIENT_CONTACT.fields_by_name['relationship'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREPATIENT_CONTACT.fields_by_name['name'].message_type = proto_dot_stu3_dot_datatypes__pb2._HUMANNAME _USCOREPATIENT_CONTACT.fields_by_name['telecom'].message_type = proto_dot_stu3_dot_datatypes__pb2._CONTACTPOINT _USCOREPATIENT_CONTACT.fields_by_name['address'].message_type = proto_dot_stu3_dot_datatypes__pb2._ADDRESS _USCOREPATIENT_CONTACT.fields_by_name['gender'].message_type = proto_dot_stu3_dot_codes__pb2._ADMINISTRATIVEGENDERCODE _USCOREPATIENT_CONTACT.fields_by_name['organization'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREPATIENT_CONTACT.fields_by_name['period'].message_type = proto_dot_stu3_dot_datatypes__pb2._PERIOD _USCOREPATIENT_CONTACT.containing_type = _USCOREPATIENT _USCOREPATIENT_COMMUNICATION.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREPATIENT_COMMUNICATION.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREPATIENT_COMMUNICATION.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREPATIENT_COMMUNICATION.fields_by_name['language'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREPATIENT_COMMUNICATION.fields_by_name['preferred'].message_type = proto_dot_stu3_dot_datatypes__pb2._BOOLEAN _USCOREPATIENT_COMMUNICATION.containing_type = _USCOREPATIENT _USCOREPATIENT_LINK.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREPATIENT_LINK.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREPATIENT_LINK.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREPATIENT_LINK.fields_by_name['other'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREPATIENT_LINK.fields_by_name['type'].message_type = proto_dot_stu3_dot_codes__pb2._LINKTYPECODE _USCOREPATIENT_LINK.containing_type = _USCOREPATIENT _USCOREPATIENT.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._ID _USCOREPATIENT.fields_by_name['meta'].message_type = proto_dot_stu3_dot_datatypes__pb2._META _USCOREPATIENT.fields_by_name['implicit_rules'].message_type = proto_dot_stu3_dot_datatypes__pb2._URI _USCOREPATIENT.fields_by_name['language'].message_type = proto_dot_stu3_dot_datatypes__pb2._LANGUAGECODE _USCOREPATIENT.fields_by_name['text'].message_type = proto_dot_stu3_dot_metadatatypes__pb2._NARRATIVE _USCOREPATIENT.fields_by_name['contained'].message_type = proto_dot_stu3_dot_resources__pb2._CONTAINEDRESOURCE _USCOREPATIENT.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREPATIENT.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREPATIENT.fields_by_name['identifier'].message_type = proto_dot_stu3_dot_datatypes__pb2._IDENTIFIER _USCOREPATIENT.fields_by_name['active'].message_type = proto_dot_stu3_dot_datatypes__pb2._BOOLEAN _USCOREPATIENT.fields_by_name['name'].message_type = proto_dot_stu3_dot_datatypes__pb2._HUMANNAME _USCOREPATIENT.fields_by_name['telecom'].message_type = proto_dot_stu3_dot_datatypes__pb2._CONTACTPOINT _USCOREPATIENT.fields_by_name['gender'].message_type = proto_dot_stu3_dot_codes__pb2._ADMINISTRATIVEGENDERCODE _USCOREPATIENT.fields_by_name['birth_date'].message_type = proto_dot_stu3_dot_datatypes__pb2._DATE _USCOREPATIENT.fields_by_name['deceased'].message_type = _USCOREPATIENT_DECEASED _USCOREPATIENT.fields_by_name['address'].message_type = proto_dot_stu3_dot_datatypes__pb2._ADDRESS _USCOREPATIENT.fields_by_name['marital_status'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREPATIENT.fields_by_name['multiple_birth'].message_type = _USCOREPATIENT_MULTIPLEBIRTH _USCOREPATIENT.fields_by_name['photo'].message_type = proto_dot_stu3_dot_datatypes__pb2._ATTACHMENT _USCOREPATIENT.fields_by_name['contact'].message_type = _USCOREPATIENT_CONTACT _USCOREPATIENT.fields_by_name['communication'].message_type = _USCOREPATIENT_COMMUNICATION _USCOREPATIENT.fields_by_name['general_practitioner'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREPATIENT.fields_by_name['managing_organization'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREPATIENT.fields_by_name['link'].message_type = _USCOREPATIENT_LINK _USCOREPATIENT.fields_by_name['race'].message_type = _PATIENTUSCORERACEEXTENSION _USCOREPATIENT.fields_by_name['ethnicity'].message_type = _PATIENTUSCOREETHNICITYEXTENSION _USCOREPATIENT.fields_by_name['birthsex'].message_type = proto_dot_stu3_dot_uscore__codes__pb2._USCOREBIRTHSEXCODE _USCOREPRACTITIONER_QUALIFICATION.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREPRACTITIONER_QUALIFICATION.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREPRACTITIONER_QUALIFICATION.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREPRACTITIONER_QUALIFICATION.fields_by_name['identifier'].message_type = proto_dot_stu3_dot_datatypes__pb2._IDENTIFIER _USCOREPRACTITIONER_QUALIFICATION.fields_by_name['code'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREPRACTITIONER_QUALIFICATION.fields_by_name['period'].message_type = proto_dot_stu3_dot_datatypes__pb2._PERIOD _USCOREPRACTITIONER_QUALIFICATION.fields_by_name['issuer'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREPRACTITIONER_QUALIFICATION.containing_type = _USCOREPRACTITIONER _USCOREPRACTITIONER.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._ID _USCOREPRACTITIONER.fields_by_name['meta'].message_type = proto_dot_stu3_dot_datatypes__pb2._META _USCOREPRACTITIONER.fields_by_name['implicit_rules'].message_type = proto_dot_stu3_dot_datatypes__pb2._URI _USCOREPRACTITIONER.fields_by_name['language'].message_type = proto_dot_stu3_dot_datatypes__pb2._LANGUAGECODE _USCOREPRACTITIONER.fields_by_name['text'].message_type = proto_dot_stu3_dot_metadatatypes__pb2._NARRATIVE _USCOREPRACTITIONER.fields_by_name['contained'].message_type = proto_dot_stu3_dot_resources__pb2._CONTAINEDRESOURCE _USCOREPRACTITIONER.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREPRACTITIONER.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREPRACTITIONER.fields_by_name['identifier'].message_type = proto_dot_stu3_dot_datatypes__pb2._IDENTIFIER _USCOREPRACTITIONER.fields_by_name['active'].message_type = proto_dot_stu3_dot_datatypes__pb2._BOOLEAN _USCOREPRACTITIONER.fields_by_name['name'].message_type = proto_dot_stu3_dot_datatypes__pb2._HUMANNAME _USCOREPRACTITIONER.fields_by_name['telecom'].message_type = proto_dot_stu3_dot_datatypes__pb2._CONTACTPOINT _USCOREPRACTITIONER.fields_by_name['address'].message_type = proto_dot_stu3_dot_datatypes__pb2._ADDRESS _USCOREPRACTITIONER.fields_by_name['gender'].message_type = proto_dot_stu3_dot_codes__pb2._ADMINISTRATIVEGENDERCODE _USCOREPRACTITIONER.fields_by_name['birth_date'].message_type = proto_dot_stu3_dot_datatypes__pb2._DATE _USCOREPRACTITIONER.fields_by_name['photo'].message_type = proto_dot_stu3_dot_datatypes__pb2._ATTACHMENT _USCOREPRACTITIONER.fields_by_name['qualification'].message_type = _USCOREPRACTITIONER_QUALIFICATION _USCOREPRACTITIONER.fields_by_name['communication'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREPROCEDURE_PERFORMED.fields_by_name['date_time'].message_type = proto_dot_stu3_dot_datatypes__pb2._DATETIME _USCOREPROCEDURE_PERFORMED.fields_by_name['period'].message_type = proto_dot_stu3_dot_datatypes__pb2._PERIOD _USCOREPROCEDURE_PERFORMED.containing_type = _USCOREPROCEDURE _USCOREPROCEDURE_PERFORMED.oneofs_by_name['performed'].fields.append( _USCOREPROCEDURE_PERFORMED.fields_by_name['date_time']) _USCOREPROCEDURE_PERFORMED.fields_by_name['date_time'].containing_oneof = _USCOREPROCEDURE_PERFORMED.oneofs_by_name['performed'] _USCOREPROCEDURE_PERFORMED.oneofs_by_name['performed'].fields.append( _USCOREPROCEDURE_PERFORMED.fields_by_name['period']) _USCOREPROCEDURE_PERFORMED.fields_by_name['period'].containing_oneof = _USCOREPROCEDURE_PERFORMED.oneofs_by_name['performed'] _USCOREPROCEDURE_PERFORMER.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREPROCEDURE_PERFORMER.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREPROCEDURE_PERFORMER.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREPROCEDURE_PERFORMER.fields_by_name['role'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREPROCEDURE_PERFORMER.fields_by_name['actor'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREPROCEDURE_PERFORMER.fields_by_name['on_behalf_of'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREPROCEDURE_PERFORMER.containing_type = _USCOREPROCEDURE _USCOREPROCEDURE_FOCALDEVICE.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCOREPROCEDURE_FOCALDEVICE.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREPROCEDURE_FOCALDEVICE.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREPROCEDURE_FOCALDEVICE.fields_by_name['action'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREPROCEDURE_FOCALDEVICE.fields_by_name['manipulated'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREPROCEDURE_FOCALDEVICE.containing_type = _USCOREPROCEDURE _USCOREPROCEDURE.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._ID _USCOREPROCEDURE.fields_by_name['meta'].message_type = proto_dot_stu3_dot_datatypes__pb2._META _USCOREPROCEDURE.fields_by_name['implicit_rules'].message_type = proto_dot_stu3_dot_datatypes__pb2._URI _USCOREPROCEDURE.fields_by_name['language'].message_type = proto_dot_stu3_dot_datatypes__pb2._LANGUAGECODE _USCOREPROCEDURE.fields_by_name['text'].message_type = proto_dot_stu3_dot_metadatatypes__pb2._NARRATIVE _USCOREPROCEDURE.fields_by_name['contained'].message_type = proto_dot_stu3_dot_resources__pb2._CONTAINEDRESOURCE _USCOREPROCEDURE.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREPROCEDURE.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCOREPROCEDURE.fields_by_name['identifier'].message_type = proto_dot_stu3_dot_datatypes__pb2._IDENTIFIER _USCOREPROCEDURE.fields_by_name['definition'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREPROCEDURE.fields_by_name['based_on'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREPROCEDURE.fields_by_name['part_of'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREPROCEDURE.fields_by_name['status'].message_type = proto_dot_stu3_dot_codes__pb2._EVENTSTATUSCODE _USCOREPROCEDURE.fields_by_name['not_done'].message_type = proto_dot_stu3_dot_datatypes__pb2._BOOLEAN _USCOREPROCEDURE.fields_by_name['not_done_reason'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREPROCEDURE.fields_by_name['category'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREPROCEDURE.fields_by_name['code'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREPROCEDURE.fields_by_name['subject'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREPROCEDURE.fields_by_name['context'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREPROCEDURE.fields_by_name['performed'].message_type = _USCOREPROCEDURE_PERFORMED _USCOREPROCEDURE.fields_by_name['performer'].message_type = _USCOREPROCEDURE_PERFORMER _USCOREPROCEDURE.fields_by_name['location'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREPROCEDURE.fields_by_name['reason_code'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREPROCEDURE.fields_by_name['reason_reference'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREPROCEDURE.fields_by_name['body_site'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREPROCEDURE.fields_by_name['outcome'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREPROCEDURE.fields_by_name['report'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREPROCEDURE.fields_by_name['complication'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREPROCEDURE.fields_by_name['complication_detail'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREPROCEDURE.fields_by_name['follow_up'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCOREPROCEDURE.fields_by_name['note'].message_type = proto_dot_stu3_dot_datatypes__pb2._ANNOTATION _USCOREPROCEDURE.fields_by_name['focal_device'].message_type = _USCOREPROCEDURE_FOCALDEVICE _USCOREPROCEDURE.fields_by_name['used_reference'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCOREPROCEDURE.fields_by_name['used_code'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _CAPABILITYSTATEMENTPROFILERESOURCEASSOCIATIONEXTENSION.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _CAPABILITYSTATEMENTPROFILERESOURCEASSOCIATIONEXTENSION.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _CAPABILITYSTATEMENTPROFILERESOURCEASSOCIATIONEXTENSION.fields_by_name['value_code'].message_type = proto_dot_stu3_dot_codes__pb2._RESOURCETYPECODE _PATIENTUSCORERACEEXTENSION.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _PATIENTUSCORERACEEXTENSION.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _PATIENTUSCORERACEEXTENSION.fields_by_name['omb_category'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODING _PATIENTUSCORERACEEXTENSION.fields_by_name['detailed'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODING _PATIENTUSCORERACEEXTENSION.fields_by_name['text'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCORESMOKINGSTATUS_EFFECTIVE.fields_by_name['date_time'].message_type = proto_dot_stu3_dot_datatypes__pb2._DATETIME _USCORESMOKINGSTATUS_EFFECTIVE.fields_by_name['period'].message_type = proto_dot_stu3_dot_datatypes__pb2._PERIOD _USCORESMOKINGSTATUS_EFFECTIVE.containing_type = _USCORESMOKINGSTATUS _USCORESMOKINGSTATUS_EFFECTIVE.oneofs_by_name['effective'].fields.append( _USCORESMOKINGSTATUS_EFFECTIVE.fields_by_name['date_time']) _USCORESMOKINGSTATUS_EFFECTIVE.fields_by_name['date_time'].containing_oneof = _USCORESMOKINGSTATUS_EFFECTIVE.oneofs_by_name['effective'] _USCORESMOKINGSTATUS_EFFECTIVE.oneofs_by_name['effective'].fields.append( _USCORESMOKINGSTATUS_EFFECTIVE.fields_by_name['period']) _USCORESMOKINGSTATUS_EFFECTIVE.fields_by_name['period'].containing_oneof = _USCORESMOKINGSTATUS_EFFECTIVE.oneofs_by_name['effective'] _USCORESMOKINGSTATUS_VALUE.fields_by_name['codeable_concept'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCORESMOKINGSTATUS_VALUE.containing_type = _USCORESMOKINGSTATUS _USCORESMOKINGSTATUS_VALUE.oneofs_by_name['value'].fields.append( _USCORESMOKINGSTATUS_VALUE.fields_by_name['codeable_concept']) _USCORESMOKINGSTATUS_VALUE.fields_by_name['codeable_concept'].containing_oneof = _USCORESMOKINGSTATUS_VALUE.oneofs_by_name['value'] _USCORESMOKINGSTATUS_REFERENCERANGE.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCORESMOKINGSTATUS_REFERENCERANGE.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCORESMOKINGSTATUS_REFERENCERANGE.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCORESMOKINGSTATUS_REFERENCERANGE.fields_by_name['low'].message_type = proto_dot_stu3_dot_datatypes__pb2._SIMPLEQUANTITY _USCORESMOKINGSTATUS_REFERENCERANGE.fields_by_name['high'].message_type = proto_dot_stu3_dot_datatypes__pb2._SIMPLEQUANTITY _USCORESMOKINGSTATUS_REFERENCERANGE.fields_by_name['type'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCORESMOKINGSTATUS_REFERENCERANGE.fields_by_name['applies_to'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCORESMOKINGSTATUS_REFERENCERANGE.fields_by_name['age'].message_type = proto_dot_stu3_dot_datatypes__pb2._RANGE _USCORESMOKINGSTATUS_REFERENCERANGE.fields_by_name['text'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCORESMOKINGSTATUS_REFERENCERANGE.containing_type = _USCORESMOKINGSTATUS _USCORESMOKINGSTATUS_RELATED.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCORESMOKINGSTATUS_RELATED.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCORESMOKINGSTATUS_RELATED.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCORESMOKINGSTATUS_RELATED.fields_by_name['type'].message_type = proto_dot_stu3_dot_codes__pb2._OBSERVATIONRELATIONSHIPTYPECODE _USCORESMOKINGSTATUS_RELATED.fields_by_name['target'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORESMOKINGSTATUS_RELATED.containing_type = _USCORESMOKINGSTATUS _USCORESMOKINGSTATUS_COMPONENT_VALUE.fields_by_name['quantity'].message_type = proto_dot_stu3_dot_datatypes__pb2._QUANTITY _USCORESMOKINGSTATUS_COMPONENT_VALUE.fields_by_name['codeable_concept'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCORESMOKINGSTATUS_COMPONENT_VALUE.fields_by_name['string_value'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCORESMOKINGSTATUS_COMPONENT_VALUE.fields_by_name['range'].message_type = proto_dot_stu3_dot_datatypes__pb2._RANGE _USCORESMOKINGSTATUS_COMPONENT_VALUE.fields_by_name['ratio'].message_type = proto_dot_stu3_dot_datatypes__pb2._RATIO _USCORESMOKINGSTATUS_COMPONENT_VALUE.fields_by_name['sampled_data'].message_type = proto_dot_stu3_dot_datatypes__pb2._SAMPLEDDATA _USCORESMOKINGSTATUS_COMPONENT_VALUE.fields_by_name['attachment'].message_type = proto_dot_stu3_dot_datatypes__pb2._ATTACHMENT _USCORESMOKINGSTATUS_COMPONENT_VALUE.fields_by_name['time'].message_type = proto_dot_stu3_dot_datatypes__pb2._TIME _USCORESMOKINGSTATUS_COMPONENT_VALUE.fields_by_name['date_time'].message_type = proto_dot_stu3_dot_datatypes__pb2._DATETIME _USCORESMOKINGSTATUS_COMPONENT_VALUE.fields_by_name['period'].message_type = proto_dot_stu3_dot_datatypes__pb2._PERIOD _USCORESMOKINGSTATUS_COMPONENT_VALUE.containing_type = _USCORESMOKINGSTATUS_COMPONENT _USCORESMOKINGSTATUS_COMPONENT_VALUE.oneofs_by_name['value'].fields.append( _USCORESMOKINGSTATUS_COMPONENT_VALUE.fields_by_name['quantity']) _USCORESMOKINGSTATUS_COMPONENT_VALUE.fields_by_name['quantity'].containing_oneof = _USCORESMOKINGSTATUS_COMPONENT_VALUE.oneofs_by_name['value'] _USCORESMOKINGSTATUS_COMPONENT_VALUE.oneofs_by_name['value'].fields.append( _USCORESMOKINGSTATUS_COMPONENT_VALUE.fields_by_name['codeable_concept']) _USCORESMOKINGSTATUS_COMPONENT_VALUE.fields_by_name['codeable_concept'].containing_oneof = _USCORESMOKINGSTATUS_COMPONENT_VALUE.oneofs_by_name['value'] _USCORESMOKINGSTATUS_COMPONENT_VALUE.oneofs_by_name['value'].fields.append( _USCORESMOKINGSTATUS_COMPONENT_VALUE.fields_by_name['string_value']) _USCORESMOKINGSTATUS_COMPONENT_VALUE.fields_by_name['string_value'].containing_oneof = _USCORESMOKINGSTATUS_COMPONENT_VALUE.oneofs_by_name['value'] _USCORESMOKINGSTATUS_COMPONENT_VALUE.oneofs_by_name['value'].fields.append( _USCORESMOKINGSTATUS_COMPONENT_VALUE.fields_by_name['range']) _USCORESMOKINGSTATUS_COMPONENT_VALUE.fields_by_name['range'].containing_oneof = _USCORESMOKINGSTATUS_COMPONENT_VALUE.oneofs_by_name['value'] _USCORESMOKINGSTATUS_COMPONENT_VALUE.oneofs_by_name['value'].fields.append( _USCORESMOKINGSTATUS_COMPONENT_VALUE.fields_by_name['ratio']) _USCORESMOKINGSTATUS_COMPONENT_VALUE.fields_by_name['ratio'].containing_oneof = _USCORESMOKINGSTATUS_COMPONENT_VALUE.oneofs_by_name['value'] _USCORESMOKINGSTATUS_COMPONENT_VALUE.oneofs_by_name['value'].fields.append( _USCORESMOKINGSTATUS_COMPONENT_VALUE.fields_by_name['sampled_data']) _USCORESMOKINGSTATUS_COMPONENT_VALUE.fields_by_name['sampled_data'].containing_oneof = _USCORESMOKINGSTATUS_COMPONENT_VALUE.oneofs_by_name['value'] _USCORESMOKINGSTATUS_COMPONENT_VALUE.oneofs_by_name['value'].fields.append( _USCORESMOKINGSTATUS_COMPONENT_VALUE.fields_by_name['attachment']) _USCORESMOKINGSTATUS_COMPONENT_VALUE.fields_by_name['attachment'].containing_oneof = _USCORESMOKINGSTATUS_COMPONENT_VALUE.oneofs_by_name['value'] _USCORESMOKINGSTATUS_COMPONENT_VALUE.oneofs_by_name['value'].fields.append( _USCORESMOKINGSTATUS_COMPONENT_VALUE.fields_by_name['time']) _USCORESMOKINGSTATUS_COMPONENT_VALUE.fields_by_name['time'].containing_oneof = _USCORESMOKINGSTATUS_COMPONENT_VALUE.oneofs_by_name['value'] _USCORESMOKINGSTATUS_COMPONENT_VALUE.oneofs_by_name['value'].fields.append( _USCORESMOKINGSTATUS_COMPONENT_VALUE.fields_by_name['date_time']) _USCORESMOKINGSTATUS_COMPONENT_VALUE.fields_by_name['date_time'].containing_oneof = _USCORESMOKINGSTATUS_COMPONENT_VALUE.oneofs_by_name['value'] _USCORESMOKINGSTATUS_COMPONENT_VALUE.oneofs_by_name['value'].fields.append( _USCORESMOKINGSTATUS_COMPONENT_VALUE.fields_by_name['period']) _USCORESMOKINGSTATUS_COMPONENT_VALUE.fields_by_name['period'].containing_oneof = _USCORESMOKINGSTATUS_COMPONENT_VALUE.oneofs_by_name['value'] _USCORESMOKINGSTATUS_COMPONENT.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCORESMOKINGSTATUS_COMPONENT.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCORESMOKINGSTATUS_COMPONENT.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCORESMOKINGSTATUS_COMPONENT.fields_by_name['code'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCORESMOKINGSTATUS_COMPONENT.fields_by_name['value'].message_type = _USCORESMOKINGSTATUS_COMPONENT_VALUE _USCORESMOKINGSTATUS_COMPONENT.fields_by_name['data_absent_reason'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCORESMOKINGSTATUS_COMPONENT.fields_by_name['interpretation'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCORESMOKINGSTATUS_COMPONENT.fields_by_name['reference_range'].message_type = _USCORESMOKINGSTATUS_REFERENCERANGE _USCORESMOKINGSTATUS_COMPONENT.containing_type = _USCORESMOKINGSTATUS _USCORESMOKINGSTATUS.fields_by_name['id'].message_type = proto_dot_stu3_dot_datatypes__pb2._ID _USCORESMOKINGSTATUS.fields_by_name['meta'].message_type = proto_dot_stu3_dot_datatypes__pb2._META _USCORESMOKINGSTATUS.fields_by_name['implicit_rules'].message_type = proto_dot_stu3_dot_datatypes__pb2._URI _USCORESMOKINGSTATUS.fields_by_name['language'].message_type = proto_dot_stu3_dot_datatypes__pb2._LANGUAGECODE _USCORESMOKINGSTATUS.fields_by_name['text'].message_type = proto_dot_stu3_dot_metadatatypes__pb2._NARRATIVE _USCORESMOKINGSTATUS.fields_by_name['contained'].message_type = proto_dot_stu3_dot_resources__pb2._CONTAINEDRESOURCE _USCORESMOKINGSTATUS.fields_by_name['extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCORESMOKINGSTATUS.fields_by_name['modifier_extension'].message_type = proto_dot_stu3_dot_datatypes__pb2._EXTENSION _USCORESMOKINGSTATUS.fields_by_name['identifier'].message_type = proto_dot_stu3_dot_datatypes__pb2._IDENTIFIER _USCORESMOKINGSTATUS.fields_by_name['based_on'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORESMOKINGSTATUS.fields_by_name['status'].message_type = proto_dot_stu3_dot_codes__pb2._OBSERVATIONSTATUSCODE _USCORESMOKINGSTATUS.fields_by_name['category'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCORESMOKINGSTATUS.fields_by_name['code'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCORESMOKINGSTATUS.fields_by_name['subject'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORESMOKINGSTATUS.fields_by_name['context'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORESMOKINGSTATUS.fields_by_name['effective'].message_type = _USCORESMOKINGSTATUS_EFFECTIVE _USCORESMOKINGSTATUS.fields_by_name['issued'].message_type = proto_dot_stu3_dot_datatypes__pb2._INSTANT _USCORESMOKINGSTATUS.fields_by_name['performer'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORESMOKINGSTATUS.fields_by_name['value'].message_type = _USCORESMOKINGSTATUS_VALUE _USCORESMOKINGSTATUS.fields_by_name['data_absent_reason'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCORESMOKINGSTATUS.fields_by_name['interpretation'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCORESMOKINGSTATUS.fields_by_name['comment'].message_type = proto_dot_stu3_dot_datatypes__pb2._STRING _USCORESMOKINGSTATUS.fields_by_name['body_site'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCORESMOKINGSTATUS.fields_by_name['method'].message_type = proto_dot_stu3_dot_datatypes__pb2._CODEABLECONCEPT _USCORESMOKINGSTATUS.fields_by_name['specimen'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORESMOKINGSTATUS.fields_by_name['device'].message_type = proto_dot_stu3_dot_datatypes__pb2._REFERENCE _USCORESMOKINGSTATUS.fields_by_name['reference_range'].message_type = _USCORESMOKINGSTATUS_REFERENCERANGE _USCORESMOKINGSTATUS.fields_by_name['related'].message_type = _USCORESMOKINGSTATUS_RELATED _USCORESMOKINGSTATUS.fields_by_name['component'].message_type = _USCORESMOKINGSTATUS_COMPONENT DESCRIPTOR.message_types_by_name['UsCoreAllergyintolerance'] = _USCOREALLERGYINTOLERANCE DESCRIPTOR.message_types_by_name['PatientUSCoreBirthSexExtension'] = _PATIENTUSCOREBIRTHSEXEXTENSION DESCRIPTOR.message_types_by_name['UsCoreCareplan'] = _USCORECAREPLAN DESCRIPTOR.message_types_by_name['UsCoreCareteam'] = _USCORECARETEAM DESCRIPTOR.message_types_by_name['UsCoreCondition'] = _USCORECONDITION DESCRIPTOR.message_types_by_name['UsCoreDevice'] = _USCOREDEVICE DESCRIPTOR.message_types_by_name['UsCoreDiagnosticreport'] = _USCOREDIAGNOSTICREPORT DESCRIPTOR.message_types_by_name['ContactPointUsCoreDirect'] = _CONTACTPOINTUSCOREDIRECT DESCRIPTOR.message_types_by_name['PatientUSCoreEthnicityExtension'] = _PATIENTUSCOREETHNICITYEXTENSION DESCRIPTOR.message_types_by_name['UsCoreGoal'] = _USCOREGOAL DESCRIPTOR.message_types_by_name['UsCoreImmunization'] = _USCOREIMMUNIZATION DESCRIPTOR.message_types_by_name['UsCoreLocation'] = _USCORELOCATION DESCRIPTOR.message_types_by_name['UsCoreMedication'] = _USCOREMEDICATION DESCRIPTOR.message_types_by_name['UsCoreMedicationrequest'] = _USCOREMEDICATIONREQUEST DESCRIPTOR.message_types_by_name['UsCoreMedicationstatement'] = _USCOREMEDICATIONSTATEMENT DESCRIPTOR.message_types_by_name['UsCoreObservationresults'] = _USCOREOBSERVATIONRESULTS DESCRIPTOR.message_types_by_name['UsCoreOrganization'] = _USCOREORGANIZATION DESCRIPTOR.message_types_by_name['UsCorePatient'] = _USCOREPATIENT DESCRIPTOR.message_types_by_name['UsCorePractitioner'] = _USCOREPRACTITIONER DESCRIPTOR.message_types_by_name['UsCoreProcedure'] = _USCOREPROCEDURE DESCRIPTOR.message_types_by_name['CapabilityStatementProfileResourceAssociationExtension'] = _CAPABILITYSTATEMENTPROFILERESOURCEASSOCIATIONEXTENSION DESCRIPTOR.message_types_by_name['PatientUSCoreRaceExtension'] = _PATIENTUSCORERACEEXTENSION DESCRIPTOR.message_types_by_name['UsCoreSmokingstatus'] = _USCORESMOKINGSTATUS _sym_db.RegisterFileDescriptor(DESCRIPTOR) UsCoreAllergyintolerance = _reflection.GeneratedProtocolMessageType('UsCoreAllergyintolerance', (_message.Message,), dict( Onset = _reflection.GeneratedProtocolMessageType('Onset', (_message.Message,), dict( DESCRIPTOR = _USCOREALLERGYINTOLERANCE_ONSET, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreAllergyintolerance.Onset) )) , Reaction = _reflection.GeneratedProtocolMessageType('Reaction', (_message.Message,), dict( DESCRIPTOR = _USCOREALLERGYINTOLERANCE_REACTION, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreAllergyintolerance.Reaction) )) , DESCRIPTOR = _USCOREALLERGYINTOLERANCE, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreAllergyintolerance) )) _sym_db.RegisterMessage(UsCoreAllergyintolerance) _sym_db.RegisterMessage(UsCoreAllergyintolerance.Onset) _sym_db.RegisterMessage(UsCoreAllergyintolerance.Reaction) PatientUSCoreBirthSexExtension = _reflection.GeneratedProtocolMessageType('PatientUSCoreBirthSexExtension', (_message.Message,), dict( DESCRIPTOR = _PATIENTUSCOREBIRTHSEXEXTENSION, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.PatientUSCoreBirthSexExtension) )) _sym_db.RegisterMessage(PatientUSCoreBirthSexExtension) UsCoreCareplan = _reflection.GeneratedProtocolMessageType('UsCoreCareplan', (_message.Message,), dict( Activity = _reflection.GeneratedProtocolMessageType('Activity', (_message.Message,), dict( Detail = _reflection.GeneratedProtocolMessageType('Detail', (_message.Message,), dict( Scheduled = _reflection.GeneratedProtocolMessageType('Scheduled', (_message.Message,), dict( DESCRIPTOR = _USCORECAREPLAN_ACTIVITY_DETAIL_SCHEDULED, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreCareplan.Activity.Detail.Scheduled) )) , Product = _reflection.GeneratedProtocolMessageType('Product', (_message.Message,), dict( DESCRIPTOR = _USCORECAREPLAN_ACTIVITY_DETAIL_PRODUCT, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreCareplan.Activity.Detail.Product) )) , DESCRIPTOR = _USCORECAREPLAN_ACTIVITY_DETAIL, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreCareplan.Activity.Detail) )) , DESCRIPTOR = _USCORECAREPLAN_ACTIVITY, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreCareplan.Activity) )) , DESCRIPTOR = _USCORECAREPLAN, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreCareplan) )) _sym_db.RegisterMessage(UsCoreCareplan) _sym_db.RegisterMessage(UsCoreCareplan.Activity) _sym_db.RegisterMessage(UsCoreCareplan.Activity.Detail) _sym_db.RegisterMessage(UsCoreCareplan.Activity.Detail.Scheduled) _sym_db.RegisterMessage(UsCoreCareplan.Activity.Detail.Product) UsCoreCareteam = _reflection.GeneratedProtocolMessageType('UsCoreCareteam', (_message.Message,), dict( Participant = _reflection.GeneratedProtocolMessageType('Participant', (_message.Message,), dict( DESCRIPTOR = _USCORECARETEAM_PARTICIPANT, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreCareteam.Participant) )) , DESCRIPTOR = _USCORECARETEAM, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreCareteam) )) _sym_db.RegisterMessage(UsCoreCareteam) _sym_db.RegisterMessage(UsCoreCareteam.Participant) UsCoreCondition = _reflection.GeneratedProtocolMessageType('UsCoreCondition', (_message.Message,), dict( Onset = _reflection.GeneratedProtocolMessageType('Onset', (_message.Message,), dict( DESCRIPTOR = _USCORECONDITION_ONSET, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreCondition.Onset) )) , Abatement = _reflection.GeneratedProtocolMessageType('Abatement', (_message.Message,), dict( DESCRIPTOR = _USCORECONDITION_ABATEMENT, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreCondition.Abatement) )) , Stage = _reflection.GeneratedProtocolMessageType('Stage', (_message.Message,), dict( DESCRIPTOR = _USCORECONDITION_STAGE, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreCondition.Stage) )) , Evidence = _reflection.GeneratedProtocolMessageType('Evidence', (_message.Message,), dict( DESCRIPTOR = _USCORECONDITION_EVIDENCE, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreCondition.Evidence) )) , DESCRIPTOR = _USCORECONDITION, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreCondition) )) _sym_db.RegisterMessage(UsCoreCondition) _sym_db.RegisterMessage(UsCoreCondition.Onset) _sym_db.RegisterMessage(UsCoreCondition.Abatement) _sym_db.RegisterMessage(UsCoreCondition.Stage) _sym_db.RegisterMessage(UsCoreCondition.Evidence) UsCoreDevice = _reflection.GeneratedProtocolMessageType('UsCoreDevice', (_message.Message,), dict( Udi = _reflection.GeneratedProtocolMessageType('Udi', (_message.Message,), dict( DESCRIPTOR = _USCOREDEVICE_UDI, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreDevice.Udi) )) , DESCRIPTOR = _USCOREDEVICE, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreDevice) )) _sym_db.RegisterMessage(UsCoreDevice) _sym_db.RegisterMessage(UsCoreDevice.Udi) UsCoreDiagnosticreport = _reflection.GeneratedProtocolMessageType('UsCoreDiagnosticreport', (_message.Message,), dict( Effective = _reflection.GeneratedProtocolMessageType('Effective', (_message.Message,), dict( DESCRIPTOR = _USCOREDIAGNOSTICREPORT_EFFECTIVE, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreDiagnosticreport.Effective) )) , Performer = _reflection.GeneratedProtocolMessageType('Performer', (_message.Message,), dict( DESCRIPTOR = _USCOREDIAGNOSTICREPORT_PERFORMER, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreDiagnosticreport.Performer) )) , Image = _reflection.GeneratedProtocolMessageType('Image', (_message.Message,), dict( DESCRIPTOR = _USCOREDIAGNOSTICREPORT_IMAGE, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreDiagnosticreport.Image) )) , DESCRIPTOR = _USCOREDIAGNOSTICREPORT, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreDiagnosticreport) )) _sym_db.RegisterMessage(UsCoreDiagnosticreport) _sym_db.RegisterMessage(UsCoreDiagnosticreport.Effective) _sym_db.RegisterMessage(UsCoreDiagnosticreport.Performer) _sym_db.RegisterMessage(UsCoreDiagnosticreport.Image) ContactPointUsCoreDirect = _reflection.GeneratedProtocolMessageType('ContactPointUsCoreDirect', (_message.Message,), dict( DESCRIPTOR = _CONTACTPOINTUSCOREDIRECT, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.ContactPointUsCoreDirect) )) _sym_db.RegisterMessage(ContactPointUsCoreDirect) PatientUSCoreEthnicityExtension = _reflection.GeneratedProtocolMessageType('PatientUSCoreEthnicityExtension', (_message.Message,), dict( DESCRIPTOR = _PATIENTUSCOREETHNICITYEXTENSION, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.PatientUSCoreEthnicityExtension) )) _sym_db.RegisterMessage(PatientUSCoreEthnicityExtension) UsCoreGoal = _reflection.GeneratedProtocolMessageType('UsCoreGoal', (_message.Message,), dict( Start = _reflection.GeneratedProtocolMessageType('Start', (_message.Message,), dict( DESCRIPTOR = _USCOREGOAL_START, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreGoal.Start) )) , Target = _reflection.GeneratedProtocolMessageType('Target', (_message.Message,), dict( Detail = _reflection.GeneratedProtocolMessageType('Detail', (_message.Message,), dict( DESCRIPTOR = _USCOREGOAL_TARGET_DETAIL, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreGoal.Target.Detail) )) , Due = _reflection.GeneratedProtocolMessageType('Due', (_message.Message,), dict( DESCRIPTOR = _USCOREGOAL_TARGET_DUE, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreGoal.Target.Due) )) , DESCRIPTOR = _USCOREGOAL_TARGET, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreGoal.Target) )) , DESCRIPTOR = _USCOREGOAL, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreGoal) )) _sym_db.RegisterMessage(UsCoreGoal) _sym_db.RegisterMessage(UsCoreGoal.Start) _sym_db.RegisterMessage(UsCoreGoal.Target) _sym_db.RegisterMessage(UsCoreGoal.Target.Detail) _sym_db.RegisterMessage(UsCoreGoal.Target.Due) UsCoreImmunization = _reflection.GeneratedProtocolMessageType('UsCoreImmunization', (_message.Message,), dict( Practitioner = _reflection.GeneratedProtocolMessageType('Practitioner', (_message.Message,), dict( DESCRIPTOR = _USCOREIMMUNIZATION_PRACTITIONER, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreImmunization.Practitioner) )) , Explanation = _reflection.GeneratedProtocolMessageType('Explanation', (_message.Message,), dict( DESCRIPTOR = _USCOREIMMUNIZATION_EXPLANATION, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreImmunization.Explanation) )) , Reaction = _reflection.GeneratedProtocolMessageType('Reaction', (_message.Message,), dict( DESCRIPTOR = _USCOREIMMUNIZATION_REACTION, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreImmunization.Reaction) )) , VaccinationProtocol = _reflection.GeneratedProtocolMessageType('VaccinationProtocol', (_message.Message,), dict( DESCRIPTOR = _USCOREIMMUNIZATION_VACCINATIONPROTOCOL, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreImmunization.VaccinationProtocol) )) , DESCRIPTOR = _USCOREIMMUNIZATION, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreImmunization) )) _sym_db.RegisterMessage(UsCoreImmunization) _sym_db.RegisterMessage(UsCoreImmunization.Practitioner) _sym_db.RegisterMessage(UsCoreImmunization.Explanation) _sym_db.RegisterMessage(UsCoreImmunization.Reaction) _sym_db.RegisterMessage(UsCoreImmunization.VaccinationProtocol) UsCoreLocation = _reflection.GeneratedProtocolMessageType('UsCoreLocation', (_message.Message,), dict( Position = _reflection.GeneratedProtocolMessageType('Position', (_message.Message,), dict( DESCRIPTOR = _USCORELOCATION_POSITION, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreLocation.Position) )) , DESCRIPTOR = _USCORELOCATION, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreLocation) )) _sym_db.RegisterMessage(UsCoreLocation) _sym_db.RegisterMessage(UsCoreLocation.Position) UsCoreMedication = _reflection.GeneratedProtocolMessageType('UsCoreMedication', (_message.Message,), dict( Ingredient = _reflection.GeneratedProtocolMessageType('Ingredient', (_message.Message,), dict( Item = _reflection.GeneratedProtocolMessageType('Item', (_message.Message,), dict( DESCRIPTOR = _USCOREMEDICATION_INGREDIENT_ITEM, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreMedication.Ingredient.Item) )) , DESCRIPTOR = _USCOREMEDICATION_INGREDIENT, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreMedication.Ingredient) )) , Package = _reflection.GeneratedProtocolMessageType('Package', (_message.Message,), dict( Content = _reflection.GeneratedProtocolMessageType('Content', (_message.Message,), dict( Item = _reflection.GeneratedProtocolMessageType('Item', (_message.Message,), dict( DESCRIPTOR = _USCOREMEDICATION_PACKAGE_CONTENT_ITEM, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreMedication.Package.Content.Item) )) , DESCRIPTOR = _USCOREMEDICATION_PACKAGE_CONTENT, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreMedication.Package.Content) )) , Batch = _reflection.GeneratedProtocolMessageType('Batch', (_message.Message,), dict( DESCRIPTOR = _USCOREMEDICATION_PACKAGE_BATCH, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreMedication.Package.Batch) )) , DESCRIPTOR = _USCOREMEDICATION_PACKAGE, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreMedication.Package) )) , DESCRIPTOR = _USCOREMEDICATION, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreMedication) )) _sym_db.RegisterMessage(UsCoreMedication) _sym_db.RegisterMessage(UsCoreMedication.Ingredient) _sym_db.RegisterMessage(UsCoreMedication.Ingredient.Item) _sym_db.RegisterMessage(UsCoreMedication.Package) _sym_db.RegisterMessage(UsCoreMedication.Package.Content) _sym_db.RegisterMessage(UsCoreMedication.Package.Content.Item) _sym_db.RegisterMessage(UsCoreMedication.Package.Batch) UsCoreMedicationrequest = _reflection.GeneratedProtocolMessageType('UsCoreMedicationrequest', (_message.Message,), dict( Medication = _reflection.GeneratedProtocolMessageType('Medication', (_message.Message,), dict( DESCRIPTOR = _USCOREMEDICATIONREQUEST_MEDICATION, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreMedicationrequest.Medication) )) , Requester = _reflection.GeneratedProtocolMessageType('Requester', (_message.Message,), dict( DESCRIPTOR = _USCOREMEDICATIONREQUEST_REQUESTER, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreMedicationrequest.Requester) )) , DispenseRequest = _reflection.GeneratedProtocolMessageType('DispenseRequest', (_message.Message,), dict( DESCRIPTOR = _USCOREMEDICATIONREQUEST_DISPENSEREQUEST, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreMedicationrequest.DispenseRequest) )) , Substitution = _reflection.GeneratedProtocolMessageType('Substitution', (_message.Message,), dict( DESCRIPTOR = _USCOREMEDICATIONREQUEST_SUBSTITUTION, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreMedicationrequest.Substitution) )) , DESCRIPTOR = _USCOREMEDICATIONREQUEST, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreMedicationrequest) )) _sym_db.RegisterMessage(UsCoreMedicationrequest) _sym_db.RegisterMessage(UsCoreMedicationrequest.Medication) _sym_db.RegisterMessage(UsCoreMedicationrequest.Requester) _sym_db.RegisterMessage(UsCoreMedicationrequest.DispenseRequest) _sym_db.RegisterMessage(UsCoreMedicationrequest.Substitution) UsCoreMedicationstatement = _reflection.GeneratedProtocolMessageType('UsCoreMedicationstatement', (_message.Message,), dict( Medication = _reflection.GeneratedProtocolMessageType('Medication', (_message.Message,), dict( DESCRIPTOR = _USCOREMEDICATIONSTATEMENT_MEDICATION, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreMedicationstatement.Medication) )) , Effective = _reflection.GeneratedProtocolMessageType('Effective', (_message.Message,), dict( DESCRIPTOR = _USCOREMEDICATIONSTATEMENT_EFFECTIVE, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreMedicationstatement.Effective) )) , DESCRIPTOR = _USCOREMEDICATIONSTATEMENT, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreMedicationstatement) )) _sym_db.RegisterMessage(UsCoreMedicationstatement) _sym_db.RegisterMessage(UsCoreMedicationstatement.Medication) _sym_db.RegisterMessage(UsCoreMedicationstatement.Effective) UsCoreObservationresults = _reflection.GeneratedProtocolMessageType('UsCoreObservationresults', (_message.Message,), dict( Effective = _reflection.GeneratedProtocolMessageType('Effective', (_message.Message,), dict( DESCRIPTOR = _USCOREOBSERVATIONRESULTS_EFFECTIVE, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreObservationresults.Effective) )) , Value = _reflection.GeneratedProtocolMessageType('Value', (_message.Message,), dict( DESCRIPTOR = _USCOREOBSERVATIONRESULTS_VALUE, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreObservationresults.Value) )) , ReferenceRange = _reflection.GeneratedProtocolMessageType('ReferenceRange', (_message.Message,), dict( DESCRIPTOR = _USCOREOBSERVATIONRESULTS_REFERENCERANGE, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreObservationresults.ReferenceRange) )) , Related = _reflection.GeneratedProtocolMessageType('Related', (_message.Message,), dict( DESCRIPTOR = _USCOREOBSERVATIONRESULTS_RELATED, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreObservationresults.Related) )) , Component = _reflection.GeneratedProtocolMessageType('Component', (_message.Message,), dict( Value = _reflection.GeneratedProtocolMessageType('Value', (_message.Message,), dict( DESCRIPTOR = _USCOREOBSERVATIONRESULTS_COMPONENT_VALUE, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreObservationresults.Component.Value) )) , DESCRIPTOR = _USCOREOBSERVATIONRESULTS_COMPONENT, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreObservationresults.Component) )) , DESCRIPTOR = _USCOREOBSERVATIONRESULTS, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreObservationresults) )) _sym_db.RegisterMessage(UsCoreObservationresults) _sym_db.RegisterMessage(UsCoreObservationresults.Effective) _sym_db.RegisterMessage(UsCoreObservationresults.Value) _sym_db.RegisterMessage(UsCoreObservationresults.ReferenceRange) _sym_db.RegisterMessage(UsCoreObservationresults.Related) _sym_db.RegisterMessage(UsCoreObservationresults.Component) _sym_db.RegisterMessage(UsCoreObservationresults.Component.Value) UsCoreOrganization = _reflection.GeneratedProtocolMessageType('UsCoreOrganization', (_message.Message,), dict( Contact = _reflection.GeneratedProtocolMessageType('Contact', (_message.Message,), dict( DESCRIPTOR = _USCOREORGANIZATION_CONTACT, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreOrganization.Contact) )) , DESCRIPTOR = _USCOREORGANIZATION, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreOrganization) )) _sym_db.RegisterMessage(UsCoreOrganization) _sym_db.RegisterMessage(UsCoreOrganization.Contact) UsCorePatient = _reflection.GeneratedProtocolMessageType('UsCorePatient', (_message.Message,), dict( Deceased = _reflection.GeneratedProtocolMessageType('Deceased', (_message.Message,), dict( DESCRIPTOR = _USCOREPATIENT_DECEASED, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCorePatient.Deceased) )) , MultipleBirth = _reflection.GeneratedProtocolMessageType('MultipleBirth', (_message.Message,), dict( DESCRIPTOR = _USCOREPATIENT_MULTIPLEBIRTH, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCorePatient.MultipleBirth) )) , Contact = _reflection.GeneratedProtocolMessageType('Contact', (_message.Message,), dict( DESCRIPTOR = _USCOREPATIENT_CONTACT, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCorePatient.Contact) )) , Communication = _reflection.GeneratedProtocolMessageType('Communication', (_message.Message,), dict( DESCRIPTOR = _USCOREPATIENT_COMMUNICATION, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCorePatient.Communication) )) , Link = _reflection.GeneratedProtocolMessageType('Link', (_message.Message,), dict( DESCRIPTOR = _USCOREPATIENT_LINK, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCorePatient.Link) )) , DESCRIPTOR = _USCOREPATIENT, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCorePatient) )) _sym_db.RegisterMessage(UsCorePatient) _sym_db.RegisterMessage(UsCorePatient.Deceased) _sym_db.RegisterMessage(UsCorePatient.MultipleBirth) _sym_db.RegisterMessage(UsCorePatient.Contact) _sym_db.RegisterMessage(UsCorePatient.Communication) _sym_db.RegisterMessage(UsCorePatient.Link) UsCorePractitioner = _reflection.GeneratedProtocolMessageType('UsCorePractitioner', (_message.Message,), dict( Qualification = _reflection.GeneratedProtocolMessageType('Qualification', (_message.Message,), dict( DESCRIPTOR = _USCOREPRACTITIONER_QUALIFICATION, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCorePractitioner.Qualification) )) , DESCRIPTOR = _USCOREPRACTITIONER, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCorePractitioner) )) _sym_db.RegisterMessage(UsCorePractitioner) _sym_db.RegisterMessage(UsCorePractitioner.Qualification) UsCoreProcedure = _reflection.GeneratedProtocolMessageType('UsCoreProcedure', (_message.Message,), dict( Performed = _reflection.GeneratedProtocolMessageType('Performed', (_message.Message,), dict( DESCRIPTOR = _USCOREPROCEDURE_PERFORMED, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreProcedure.Performed) )) , Performer = _reflection.GeneratedProtocolMessageType('Performer', (_message.Message,), dict( DESCRIPTOR = _USCOREPROCEDURE_PERFORMER, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreProcedure.Performer) )) , FocalDevice = _reflection.GeneratedProtocolMessageType('FocalDevice', (_message.Message,), dict( DESCRIPTOR = _USCOREPROCEDURE_FOCALDEVICE, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreProcedure.FocalDevice) )) , DESCRIPTOR = _USCOREPROCEDURE, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreProcedure) )) _sym_db.RegisterMessage(UsCoreProcedure) _sym_db.RegisterMessage(UsCoreProcedure.Performed) _sym_db.RegisterMessage(UsCoreProcedure.Performer) _sym_db.RegisterMessage(UsCoreProcedure.FocalDevice) CapabilityStatementProfileResourceAssociationExtension = _reflection.GeneratedProtocolMessageType('CapabilityStatementProfileResourceAssociationExtension', (_message.Message,), dict( DESCRIPTOR = _CAPABILITYSTATEMENTPROFILERESOURCEASSOCIATIONEXTENSION, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.CapabilityStatementProfileResourceAssociationExtension) )) _sym_db.RegisterMessage(CapabilityStatementProfileResourceAssociationExtension) PatientUSCoreRaceExtension = _reflection.GeneratedProtocolMessageType('PatientUSCoreRaceExtension', (_message.Message,), dict( DESCRIPTOR = _PATIENTUSCORERACEEXTENSION, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.PatientUSCoreRaceExtension) )) _sym_db.RegisterMessage(PatientUSCoreRaceExtension) UsCoreSmokingstatus = _reflection.GeneratedProtocolMessageType('UsCoreSmokingstatus', (_message.Message,), dict( Effective = _reflection.GeneratedProtocolMessageType('Effective', (_message.Message,), dict( DESCRIPTOR = _USCORESMOKINGSTATUS_EFFECTIVE, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreSmokingstatus.Effective) )) , Value = _reflection.GeneratedProtocolMessageType('Value', (_message.Message,), dict( DESCRIPTOR = _USCORESMOKINGSTATUS_VALUE, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreSmokingstatus.Value) )) , ReferenceRange = _reflection.GeneratedProtocolMessageType('ReferenceRange', (_message.Message,), dict( DESCRIPTOR = _USCORESMOKINGSTATUS_REFERENCERANGE, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreSmokingstatus.ReferenceRange) )) , Related = _reflection.GeneratedProtocolMessageType('Related', (_message.Message,), dict( DESCRIPTOR = _USCORESMOKINGSTATUS_RELATED, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreSmokingstatus.Related) )) , Component = _reflection.GeneratedProtocolMessageType('Component', (_message.Message,), dict( Value = _reflection.GeneratedProtocolMessageType('Value', (_message.Message,), dict( DESCRIPTOR = _USCORESMOKINGSTATUS_COMPONENT_VALUE, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreSmokingstatus.Component.Value) )) , DESCRIPTOR = _USCORESMOKINGSTATUS_COMPONENT, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreSmokingstatus.Component) )) , DESCRIPTOR = _USCORESMOKINGSTATUS, __module__ = 'proto.stu3.uscore_pb2' # @@protoc_insertion_point(class_scope:google.fhir.stu3.uscore.UsCoreSmokingstatus) )) _sym_db.RegisterMessage(UsCoreSmokingstatus) _sym_db.RegisterMessage(UsCoreSmokingstatus.Effective) _sym_db.RegisterMessage(UsCoreSmokingstatus.Value) _sym_db.RegisterMessage(UsCoreSmokingstatus.ReferenceRange) _sym_db.RegisterMessage(UsCoreSmokingstatus.Related) _sym_db.RegisterMessage(UsCoreSmokingstatus.Component) _sym_db.RegisterMessage(UsCoreSmokingstatus.Component.Value) DESCRIPTOR._options = None _USCOREALLERGYINTOLERANCE_REACTION.fields_by_name['manifestation']._options = None _USCOREALLERGYINTOLERANCE.fields_by_name['verification_status']._options = None _USCOREALLERGYINTOLERANCE.fields_by_name['code']._options = None _USCOREALLERGYINTOLERANCE.fields_by_name['patient']._options = None _USCOREALLERGYINTOLERANCE.fields_by_name['onset']._options = None _USCOREALLERGYINTOLERANCE.fields_by_name['recorder']._options = None _USCOREALLERGYINTOLERANCE.fields_by_name['asserter']._options = None _USCOREALLERGYINTOLERANCE._options = None _PATIENTUSCOREBIRTHSEXEXTENSION._options = None _USCORECAREPLAN_ACTIVITY_DETAIL_PRODUCT.fields_by_name['reference']._options = None _USCORECAREPLAN_ACTIVITY_DETAIL.fields_by_name['definition']._options = None _USCORECAREPLAN_ACTIVITY_DETAIL.fields_by_name['reason_reference']._options = None _USCORECAREPLAN_ACTIVITY_DETAIL.fields_by_name['goal']._options = None _USCORECAREPLAN_ACTIVITY_DETAIL.fields_by_name['status']._options = None _USCORECAREPLAN_ACTIVITY_DETAIL.fields_by_name['scheduled']._options = None _USCORECAREPLAN_ACTIVITY_DETAIL.fields_by_name['location']._options = None _USCORECAREPLAN_ACTIVITY_DETAIL.fields_by_name['performer']._options = None _USCORECAREPLAN_ACTIVITY_DETAIL.fields_by_name['product']._options = None _USCORECAREPLAN_ACTIVITY.fields_by_name['outcome_reference']._options = None _USCORECAREPLAN_ACTIVITY.fields_by_name['reference']._options = None _USCORECAREPLAN.fields_by_name['text']._options = None _USCORECAREPLAN.fields_by_name['definition']._options = None _USCORECAREPLAN.fields_by_name['based_on']._options = None _USCORECAREPLAN.fields_by_name['replaces']._options = None _USCORECAREPLAN.fields_by_name['part_of']._options = None _USCORECAREPLAN.fields_by_name['status']._options = None _USCORECAREPLAN.fields_by_name['intent']._options = None _USCORECAREPLAN.fields_by_name['category']._options = None _USCORECAREPLAN.fields_by_name['subject']._options = None _USCORECAREPLAN.fields_by_name['context']._options = None _USCORECAREPLAN.fields_by_name['author']._options = None _USCORECAREPLAN.fields_by_name['care_team']._options = None _USCORECAREPLAN.fields_by_name['addresses']._options = None _USCORECAREPLAN.fields_by_name['supporting_info']._options = None _USCORECAREPLAN.fields_by_name['goal']._options = None _USCORECAREPLAN._options = None _USCORECARETEAM_PARTICIPANT.fields_by_name['role']._options = None _USCORECARETEAM_PARTICIPANT.fields_by_name['member']._options = None _USCORECARETEAM_PARTICIPANT.fields_by_name['on_behalf_of']._options = None _USCORECARETEAM.fields_by_name['status']._options = None _USCORECARETEAM.fields_by_name['subject']._options = None _USCORECARETEAM.fields_by_name['context']._options = None _USCORECARETEAM.fields_by_name['participant']._options = None _USCORECARETEAM.fields_by_name['reason_reference']._options = None _USCORECARETEAM.fields_by_name['managing_organization']._options = None _USCORECARETEAM._options = None _USCORECONDITION_STAGE.fields_by_name['assessment']._options = None _USCORECONDITION_EVIDENCE.fields_by_name['detail']._options = None _USCORECONDITION.fields_by_name['verification_status']._options = None _USCORECONDITION.fields_by_name['category']._options = None _USCORECONDITION.fields_by_name['code']._options = None _USCORECONDITION.fields_by_name['subject']._options = None _USCORECONDITION.fields_by_name['context']._options = None _USCORECONDITION.fields_by_name['onset']._options = None _USCORECONDITION.fields_by_name['abatement']._options = None _USCORECONDITION.fields_by_name['asserter']._options = None _USCORECONDITION._options = None _USCOREDEVICE.fields_by_name['udi']._options = None _USCOREDEVICE.fields_by_name['type']._options = None _USCOREDEVICE.fields_by_name['patient']._options = None _USCOREDEVICE.fields_by_name['owner']._options = None _USCOREDEVICE.fields_by_name['location']._options = None _USCOREDEVICE._options = None _USCOREDIAGNOSTICREPORT_PERFORMER.fields_by_name['actor']._options = None _USCOREDIAGNOSTICREPORT_IMAGE.fields_by_name['link']._options = None _USCOREDIAGNOSTICREPORT.fields_by_name['based_on']._options = None _USCOREDIAGNOSTICREPORT.fields_by_name['status']._options = None _USCOREDIAGNOSTICREPORT.fields_by_name['category']._options = None _USCOREDIAGNOSTICREPORT.fields_by_name['code']._options = None _USCOREDIAGNOSTICREPORT.fields_by_name['subject']._options = None _USCOREDIAGNOSTICREPORT.fields_by_name['context']._options = None _USCOREDIAGNOSTICREPORT.fields_by_name['effective']._options = None _USCOREDIAGNOSTICREPORT.fields_by_name['issued']._options = None _USCOREDIAGNOSTICREPORT.fields_by_name['specimen']._options = None _USCOREDIAGNOSTICREPORT.fields_by_name['result']._options = None _USCOREDIAGNOSTICREPORT.fields_by_name['imaging_study']._options = None _USCOREDIAGNOSTICREPORT._options = None _CONTACTPOINTUSCOREDIRECT._options = None _PATIENTUSCOREETHNICITYEXTENSION.fields_by_name['text']._options = None _PATIENTUSCOREETHNICITYEXTENSION._options = None _USCOREGOAL_TARGET.fields_by_name['detail']._options = None _USCOREGOAL_TARGET.fields_by_name['due']._options = None _USCOREGOAL.fields_by_name['status']._options = None _USCOREGOAL.fields_by_name['description']._options = None _USCOREGOAL.fields_by_name['subject']._options = None _USCOREGOAL.fields_by_name['start']._options = None _USCOREGOAL.fields_by_name['expressed_by']._options = None _USCOREGOAL.fields_by_name['addresses']._options = None _USCOREGOAL.fields_by_name['outcome_reference']._options = None _USCOREGOAL._options = None _USCOREIMMUNIZATION_PRACTITIONER.fields_by_name['actor']._options = None _USCOREIMMUNIZATION_REACTION.fields_by_name['detail']._options = None _USCOREIMMUNIZATION_VACCINATIONPROTOCOL.fields_by_name['authority']._options = None _USCOREIMMUNIZATION_VACCINATIONPROTOCOL.fields_by_name['target_disease']._options = None _USCOREIMMUNIZATION_VACCINATIONPROTOCOL.fields_by_name['dose_status']._options = None _USCOREIMMUNIZATION.fields_by_name['status']._options = None _USCOREIMMUNIZATION.fields_by_name['not_given']._options = None _USCOREIMMUNIZATION.fields_by_name['vaccine_code']._options = None _USCOREIMMUNIZATION.fields_by_name['patient']._options = None _USCOREIMMUNIZATION.fields_by_name['encounter']._options = None _USCOREIMMUNIZATION.fields_by_name['date']._options = None _USCOREIMMUNIZATION.fields_by_name['primary_source']._options = None _USCOREIMMUNIZATION.fields_by_name['location']._options = None _USCOREIMMUNIZATION.fields_by_name['manufacturer']._options = None _USCOREIMMUNIZATION._options = None _USCORELOCATION_POSITION.fields_by_name['longitude']._options = None _USCORELOCATION_POSITION.fields_by_name['latitude']._options = None _USCORELOCATION.fields_by_name['name']._options = None _USCORELOCATION.fields_by_name['managing_organization']._options = None _USCORELOCATION.fields_by_name['part_of']._options = None _USCORELOCATION.fields_by_name['endpoint']._options = None _USCORELOCATION._options = None _USCOREMEDICATION_INGREDIENT_ITEM.fields_by_name['reference']._options = None _USCOREMEDICATION_INGREDIENT.fields_by_name['item']._options = None _USCOREMEDICATION_PACKAGE_CONTENT_ITEM.fields_by_name['reference']._options = None _USCOREMEDICATION_PACKAGE_CONTENT.fields_by_name['item']._options = None _USCOREMEDICATION.fields_by_name['code']._options = None _USCOREMEDICATION.fields_by_name['manufacturer']._options = None _USCOREMEDICATION._options = None _USCOREMEDICATIONREQUEST_MEDICATION.fields_by_name['reference']._options = None _USCOREMEDICATIONREQUEST_REQUESTER.fields_by_name['agent']._options = None _USCOREMEDICATIONREQUEST_REQUESTER.fields_by_name['on_behalf_of']._options = None _USCOREMEDICATIONREQUEST_DISPENSEREQUEST.fields_by_name['performer']._options = None _USCOREMEDICATIONREQUEST_SUBSTITUTION.fields_by_name['allowed']._options = None _USCOREMEDICATIONREQUEST.fields_by_name['definition']._options = None _USCOREMEDICATIONREQUEST.fields_by_name['based_on']._options = None _USCOREMEDICATIONREQUEST.fields_by_name['status']._options = None _USCOREMEDICATIONREQUEST.fields_by_name['intent']._options = None _USCOREMEDICATIONREQUEST.fields_by_name['medication']._options = None _USCOREMEDICATIONREQUEST.fields_by_name['subject']._options = None _USCOREMEDICATIONREQUEST.fields_by_name['context']._options = None _USCOREMEDICATIONREQUEST.fields_by_name['supporting_information']._options = None _USCOREMEDICATIONREQUEST.fields_by_name['authored_on']._options = None _USCOREMEDICATIONREQUEST.fields_by_name['requester']._options = None _USCOREMEDICATIONREQUEST.fields_by_name['recorder']._options = None _USCOREMEDICATIONREQUEST.fields_by_name['reason_reference']._options = None _USCOREMEDICATIONREQUEST.fields_by_name['prior_prescription']._options = None _USCOREMEDICATIONREQUEST.fields_by_name['detected_issue']._options = None _USCOREMEDICATIONREQUEST.fields_by_name['event_history']._options = None _USCOREMEDICATIONREQUEST._options = None _USCOREMEDICATIONSTATEMENT_MEDICATION.fields_by_name['reference']._options = None _USCOREMEDICATIONSTATEMENT.fields_by_name['based_on']._options = None _USCOREMEDICATIONSTATEMENT.fields_by_name['part_of']._options = None _USCOREMEDICATIONSTATEMENT.fields_by_name['context']._options = None _USCOREMEDICATIONSTATEMENT.fields_by_name['status']._options = None _USCOREMEDICATIONSTATEMENT.fields_by_name['medication']._options = None _USCOREMEDICATIONSTATEMENT.fields_by_name['effective']._options = None _USCOREMEDICATIONSTATEMENT.fields_by_name['date_asserted']._options = None _USCOREMEDICATIONSTATEMENT.fields_by_name['information_source']._options = None _USCOREMEDICATIONSTATEMENT.fields_by_name['subject']._options = None _USCOREMEDICATIONSTATEMENT.fields_by_name['derived_from']._options = None _USCOREMEDICATIONSTATEMENT.fields_by_name['taken']._options = None _USCOREMEDICATIONSTATEMENT.fields_by_name['reason_reference']._options = None _USCOREMEDICATIONSTATEMENT._options = None _USCOREOBSERVATIONRESULTS_RELATED.fields_by_name['target']._options = None _USCOREOBSERVATIONRESULTS_COMPONENT.fields_by_name['code']._options = None _USCOREOBSERVATIONRESULTS_COMPONENT.fields_by_name['value']._options = None _USCOREOBSERVATIONRESULTS.fields_by_name['based_on']._options = None _USCOREOBSERVATIONRESULTS.fields_by_name['status']._options = None _USCOREOBSERVATIONRESULTS.fields_by_name['category']._options = None _USCOREOBSERVATIONRESULTS.fields_by_name['code']._options = None _USCOREOBSERVATIONRESULTS.fields_by_name['subject']._options = None _USCOREOBSERVATIONRESULTS.fields_by_name['context']._options = None _USCOREOBSERVATIONRESULTS.fields_by_name['effective']._options = None _USCOREOBSERVATIONRESULTS.fields_by_name['performer']._options = None _USCOREOBSERVATIONRESULTS.fields_by_name['value']._options = None _USCOREOBSERVATIONRESULTS.fields_by_name['specimen']._options = None _USCOREOBSERVATIONRESULTS.fields_by_name['device']._options = None _USCOREOBSERVATIONRESULTS._options = None _USCOREORGANIZATION.fields_by_name['identifier']._options = None _USCOREORGANIZATION.fields_by_name['active']._options = None _USCOREORGANIZATION.fields_by_name['name']._options = None _USCOREORGANIZATION.fields_by_name['telecom']._options = None _USCOREORGANIZATION.fields_by_name['address']._options = None _USCOREORGANIZATION.fields_by_name['part_of']._options = None _USCOREORGANIZATION.fields_by_name['endpoint']._options = None _USCOREORGANIZATION._options = None _USCOREPATIENT_CONTACT.fields_by_name['organization']._options = None _USCOREPATIENT_COMMUNICATION.fields_by_name['language']._options = None _USCOREPATIENT_LINK.fields_by_name['other']._options = None _USCOREPATIENT_LINK.fields_by_name['type']._options = None _USCOREPATIENT.fields_by_name['identifier']._options = None _USCOREPATIENT.fields_by_name['name']._options = None _USCOREPATIENT.fields_by_name['gender']._options = None _USCOREPATIENT.fields_by_name['deceased']._options = None _USCOREPATIENT.fields_by_name['multiple_birth']._options = None _USCOREPATIENT.fields_by_name['general_practitioner']._options = None _USCOREPATIENT.fields_by_name['managing_organization']._options = None _USCOREPATIENT.fields_by_name['race']._options = None _USCOREPATIENT.fields_by_name['ethnicity']._options = None _USCOREPATIENT.fields_by_name['birthsex']._options = None _USCOREPATIENT._options = None _USCOREPRACTITIONER_QUALIFICATION.fields_by_name['code']._options = None _USCOREPRACTITIONER_QUALIFICATION.fields_by_name['issuer']._options = None _USCOREPRACTITIONER.fields_by_name['identifier']._options = None _USCOREPRACTITIONER.fields_by_name['name']._options = None _USCOREPRACTITIONER._options = None _USCOREPROCEDURE_PERFORMER.fields_by_name['actor']._options = None _USCOREPROCEDURE_PERFORMER.fields_by_name['on_behalf_of']._options = None _USCOREPROCEDURE_FOCALDEVICE.fields_by_name['manipulated']._options = None _USCOREPROCEDURE.fields_by_name['definition']._options = None _USCOREPROCEDURE.fields_by_name['based_on']._options = None _USCOREPROCEDURE.fields_by_name['part_of']._options = None _USCOREPROCEDURE.fields_by_name['status']._options = None _USCOREPROCEDURE.fields_by_name['code']._options = None _USCOREPROCEDURE.fields_by_name['subject']._options = None _USCOREPROCEDURE.fields_by_name['context']._options = None _USCOREPROCEDURE.fields_by_name['performed']._options = None _USCOREPROCEDURE.fields_by_name['location']._options = None _USCOREPROCEDURE.fields_by_name['reason_reference']._options = None _USCOREPROCEDURE.fields_by_name['report']._options = None _USCOREPROCEDURE.fields_by_name['complication_detail']._options = None _USCOREPROCEDURE.fields_by_name['used_reference']._options = None _USCOREPROCEDURE._options = None _CAPABILITYSTATEMENTPROFILERESOURCEASSOCIATIONEXTENSION._options = None _PATIENTUSCORERACEEXTENSION.fields_by_name['text']._options = None _PATIENTUSCORERACEEXTENSION._options = None _USCORESMOKINGSTATUS_RELATED.fields_by_name['target']._options = None _USCORESMOKINGSTATUS_COMPONENT.fields_by_name['code']._options = None _USCORESMOKINGSTATUS_COMPONENT.fields_by_name['value']._options = None _USCORESMOKINGSTATUS.fields_by_name['based_on']._options = None _USCORESMOKINGSTATUS.fields_by_name['status']._options = None _USCORESMOKINGSTATUS.fields_by_name['code']._options = None _USCORESMOKINGSTATUS.fields_by_name['subject']._options = None _USCORESMOKINGSTATUS.fields_by_name['context']._options = None _USCORESMOKINGSTATUS.fields_by_name['effective']._options = None _USCORESMOKINGSTATUS.fields_by_name['issued']._options = None _USCORESMOKINGSTATUS.fields_by_name['performer']._options = None _USCORESMOKINGSTATUS.fields_by_name['value']._options = None _USCORESMOKINGSTATUS.fields_by_name['specimen']._options = None _USCORESMOKINGSTATUS.fields_by_name['device']._options = None _USCORESMOKINGSTATUS._options = None # @@protoc_insertion_point(module_scope)

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8

9b44ca8e2acabb723df7b06f61ec4c4b2622c899

140

py

Python

loldib/getratings/models/NA/na_nami/__init__.py

koliupy/loldib

c9ab94deb07213cdc42b5a7c26467cdafaf81b7f

[ "Apache-2.0" ]

null

loldib/getratings/models/NA/na_nami/__init__.py

koliupy/loldib

c9ab94deb07213cdc42b5a7c26467cdafaf81b7f

[ "Apache-2.0" ]

null

loldib/getratings/models/NA/na_nami/__init__.py

koliupy/loldib

c9ab94deb07213cdc42b5a7c26467cdafaf81b7f

[ "Apache-2.0" ]

null

from .na_nami_top import * from .na_nami_jng import * from .na_nami_mid import * from .na_nami_bot import * from .na_nami_sup import *

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1

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0

8

32e5b17762d83aecefce3d082b6b15a41fa87600

4,307

py

Python

questionnaire/migrations/0011_auto_20200719_0844.py

Elephant34/Survey-Project

035e95471c81cd55793c75f5843448a66e48dfff

[ "MIT" ]

null

questionnaire/migrations/0011_auto_20200719_0844.py

Elephant34/Survey-Project

035e95471c81cd55793c75f5843448a66e48dfff

[ "MIT" ]

2

2021-03-19T09:43:22.000Z

2021-03-19T15:16:36.000Z

questionnaire/migrations/0011_auto_20200719_0844.py

Elephant34/Survey-Project

035e95471c81cd55793c75f5843448a66e48dfff

[ "MIT" ]

5

2020-05-02T18:23:03.000Z

2020-07-20T08:30:23.000Z

# Generated by Django 3.0.5 on 2020-07-19 07:44 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('questionnaire', '0010_gallery'), ] operations = [ migrations.AlterField( model_name='gallery', name='questionA_1', field=models.CharField(blank=True, max_length=1028), ), migrations.AlterField( model_name='gallery', name='questionB1_1', field=models.CharField(max_length=2048), ), migrations.AlterField( model_name='gallery', name='questionB1_10', field=models.CharField(max_length=2048), ), migrations.AlterField( model_name='gallery', name='questionB1_11', field=models.CharField(max_length=2048), ), migrations.AlterField( model_name='gallery', name='questionB1_12', field=models.CharField(max_length=2048), ), migrations.AlterField( model_name='gallery', name='questionB1_2', field=models.CharField(max_length=2048), ), migrations.AlterField( model_name='gallery', name='questionB1_3', field=models.CharField(max_length=2048), ), migrations.AlterField( model_name='gallery', name='questionB1_4', field=models.CharField(max_length=2048), ), migrations.AlterField( model_name='gallery', name='questionB1_5', field=models.CharField(max_length=2048), ), migrations.AlterField( model_name='gallery', name='questionB1_6', field=models.CharField(max_length=2048), ), migrations.AlterField( model_name='gallery', name='questionB1_7', field=models.CharField(max_length=2048), ), migrations.AlterField( model_name='gallery', name='questionB1_8', field=models.CharField(max_length=2048), ), migrations.AlterField( model_name='gallery', name='questionB1_9', field=models.CharField(max_length=2048), ), migrations.AlterField( model_name='response', name='questionB1_1', field=models.CharField(max_length=2048), ), migrations.AlterField( model_name='response', name='questionB1_10', field=models.CharField(max_length=2048), ), migrations.AlterField( model_name='response', name='questionB1_11', field=models.CharField(max_length=2048), ), migrations.AlterField( model_name='response', name='questionB1_12', field=models.CharField(max_length=2048), ), migrations.AlterField( model_name='response', name='questionB1_2', field=models.CharField(max_length=2048), ), migrations.AlterField( model_name='response', name='questionB1_3', field=models.CharField(max_length=2048), ), migrations.AlterField( model_name='response', name='questionB1_4', field=models.CharField(max_length=2048), ), migrations.AlterField( model_name='response', name='questionB1_5', field=models.CharField(max_length=2048), ), migrations.AlterField( model_name='response', name='questionB1_6', field=models.CharField(max_length=2048), ), migrations.AlterField( model_name='response', name='questionB1_7', field=models.CharField(max_length=2048), ), migrations.AlterField( model_name='response', name='questionB1_8', field=models.CharField(max_length=2048), ), migrations.AlterField( model_name='response', name='questionB1_9', field=models.CharField(max_length=2048), ), ]

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1

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null

0

11

fd52696b31be6a135b3217764e1246f54e8c6182

9

py

Python

examples/py36-0006-fstrings.py

jwilk-forks/python-grammar-changes

5cbc14e520fadfef8539760a4ffdbe14b9d02f39

[ "MIT" ]

8

2020-11-21T22:39:41.000Z

2022-03-13T18:45:53.000Z

examples/py36-0006-fstrings.py

jwilk-forks/python-grammar-changes

5cbc14e520fadfef8539760a4ffdbe14b9d02f39

[ "MIT" ]

1

2021-12-10T10:45:38.000Z

examples/py36-0006-fstrings.py

jwilk-forks/python-grammar-changes

5cbc14e520fadfef8539760a4ffdbe14b9d02f39

[ "MIT" ]

1

2022-02-07T11:16:38.000Z

f"{1+1}"

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true

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1

0

1

0

null

0

1

0

7

b5d0431aa060a346e0a42dcd7bb14c9a110bdeb5

92

py

Python

ipfs_common/src/ipfs_common/nodes.py

khssnv/robonomics_comm

606a5ee91cf003421138fee02bd0d0f595ceadfd

[ "BSD-3-Clause" ]

null

ipfs_common/src/ipfs_common/nodes.py

khssnv/robonomics_comm

606a5ee91cf003421138fee02bd0d0f595ceadfd

[ "BSD-3-Clause" ]

null

ipfs_common/src/ipfs_common/nodes.py

khssnv/robonomics_comm

606a5ee91cf003421138fee02bd0d0f595ceadfd

[ "BSD-3-Clause" ]

null

from . import ipfs_channel def ipfs_channel_node(): ipfs_channel.IPFSChannel().spin()

15.333333

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1

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0

7

bd112304e4a4b18aa85656be3df3511fc1e5771e

7,305

py

Python

deformable_kernels/ops/deform_kernel/modules/filter_sample_depthwise.py

yifanpu001/deformable-kernels

923e6c302801db1c968f495fc0002d2c7605c91c

[ "MIT" ]

199

2020-01-21T00:37:32.000Z

2022-03-25T13:44:45.000Z

deformable_kernels/ops/deform_kernel/modules/filter_sample_depthwise.py

yifanpu001/deformable-kernels

923e6c302801db1c968f495fc0002d2c7605c91c

[ "MIT" ]

7

2020-04-15T17:55:07.000Z

2021-06-23T14:18:57.000Z

deformable_kernels/ops/deform_kernel/modules/filter_sample_depthwise.py

yifanpu001/deformable-kernels

923e6c302801db1c968f495fc0002d2c7605c91c

[ "MIT" ]

30

2020-01-21T01:14:00.000Z

2021-12-26T23:08:57.000Z

#!/usr/bin/env python3 # # File : filter_sample_depthwise.py # Author : Hang Gao # Email : hangg.sv7@gmail.com # Date : 01/17/2020 # # Distributed under terms of the MIT license. import math import torch import torch.nn as nn from torch.nn.modules.utils import _pair from ..functions.filter_sample_depthwise import ( sample_depthwise, deform_sample_depthwise, ) __all__ = [ 'SampleDepthwise', 'DeformableSampleDepthwise', ] class SampleDepthwise(nn.Module): def __init__(self, scope_size, in_channels, out_channels, kernel_size=3, stride=1, padding=1, dilation=1, groups=1, rotation_groups=1, bias=False): super(SampleDepthwise, self).__init__() self.in_channels = in_channels assert in_channels == out_channels and groups == in_channels assert in_channels % rotation_groups == 0 and \ out_channels % rotation_groups == 0 self.scope_size = scope_size self.kernel_size = _pair(kernel_size) self.stride = _pair(stride) self.padding = _pair(padding) self.dilation = _pair(dilation) self.rotation_groups = rotation_groups self.bias = bias self.weight = nn.Parameter(torch.Tensor(self.in_channels, 1, *self.scope_size)) if not self.bias: self.bias = None else: self.bias = nn.Parameter(torch.Tensor(self.in_channels)) self.reset_parameters() def reset_parameters(self): n = 1 for k in self.kernel_size: n *= k stdv = 1. / math.sqrt(n) self.weight.data.uniform_(-stdv, stdv) if self.bias is not None: self.bias.data.zero_() def forward(self, input, rotation=None): if rotation is None: output_size = self._output_size(input, self.weight) rotation = input.new_zeros( input.size(0), self.rotation_groups * self.kernel_size[0] * self.kernel_size[1] * 2, output_size[2], output_size[3]) out = sample_depthwise( input, rotation, self.weight, self.kernel_size, self.stride, self.padding, self.dilation, self.rotation_groups) if self.bias is not None: out += self.bias.view(1, self.in_channels, 1, 1) return out def _output_size(self, input, weight): channels = weight.size(0) output_size = (input.size(0), channels) for d in range(input.dim() - 2): in_size = input.size(d + 2) pad = self.padding[d] kernel = self.dilation[d] * (self.kernel_size[d] - 1) + 1 stride = self.stride[d] output_size += ((in_size + (2 * pad) - kernel) // stride + 1, ) if not all(map(lambda s: s > 0, output_size)): raise ValueError( "convolution input is too small (output would be {})".format( 'x'.join(map(str, output_size)))) return output_size def extra_repr(self): s = ('scope_size={scope_size}, in_channels={in_channels}, ' 'kernel_size={kernel_size}, stride={stride}') if self.padding != (0,) * len(self.padding): s += ', padding={padding}' if self.dilation != (1,) * len(self.dilation): s += ', dilation={dilation}' if self.rotation_groups != 1: s += ', rotation_groups={rotation_groups}' if self.bias is None: s += ', bias=False' return s.format(**self.__dict__) class DeformableSampleDepthwise(nn.Module): def __init__(self, scope_size, in_channels, out_channels, kernel_size=3, stride=1, padding=1, dilation=1, groups=1, rotation_groups=1, bias=False): super(DeformableSampleDepthwise, self).__init__() self.in_channels = in_channels assert in_channels == out_channels and groups == in_channels assert in_channels % rotation_groups == 0 and \ out_channels % rotation_groups == 0 self.scope_size = scope_size self.kernel_size = _pair(kernel_size) self.stride = _pair(stride) self.padding = _pair(padding) self.dilation = _pair(dilation) self.rotation_groups = rotation_groups self.bias = bias self.weight = nn.Parameter(torch.Tensor(self.in_channels, 1, *self.scope_size)) if not self.bias: self.bias = None else: self.bias = nn.Parameter(torch.Tensor(self.in_channels)) self.reset_parameters() def reset_parameters(self): n = 1 for k in self.kernel_size: n *= k stdv = 1. / math.sqrt(n) self.weight.data.uniform_(-stdv, stdv) if self.bias is not None: self.bias.data.zero_() def forward(self, input, offset=None, rotation=None): if offset is None: output_size = self._output_size(input, self.weight) offset = input.new_zeros( input.size(0), self.kernel_size[0] * self.kernel_size[1] * 2, output_size[2], output_size[3]) if rotation is None: output_size = self._output_size(input, self.weight) rotation = input.new_zeros( input.size(0), self.rotation_groups * self.kernel_size[0] * self.kernel_size[1] * 2, output_size[2], output_size[3]) out = deform_sample_depthwise( input, offset, rotation, self.weight, self.kernel_size, self.stride, self.padding, self.dilation, self.rotation_groups) if self.bias is not None: out += self.bias.view(1, self.in_channels, 1, 1) return out def _output_size(self, input, weight): channels = weight.size(0) output_size = (input.size(0), channels) for d in range(input.dim() - 2): in_size = input.size(d + 2) pad = self.padding[d] kernel = self.dilation[d] * (self.kernel_size[d] - 1) + 1 stride = self.stride[d] output_size += ((in_size + (2 * pad) - kernel) // stride + 1, ) if not all(map(lambda s: s > 0, output_size)): raise ValueError( "convolution input is too small (output would be {})".format( 'x'.join(map(str, output_size)))) return output_size def extra_repr(self): s = ('scope_size={scope_size}, in_channels={in_channels}, ' 'kernel_size={kernel_size}, stride={stride}') if self.padding != (0,) * len(self.padding): s += ', padding={padding}' if self.dilation != (1,) * len(self.dilation): s += ', dilation={dilation}' if self.rotation_groups != 1: s += ', rotation_groups={rotation_groups}' if self.bias is None: s += ', bias=False' return s.format(**self.__dict__)

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null

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1

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null

0

7

bd26849c8724510245239ea5bd06d8affbf2e53e

13,212

py

Python

fhir/resources/tests/test_provenance.py

mmabey/fhir.resources

cc73718e9762c04726cd7de240c8f2dd5313cbe1

[ "BSD-3-Clause" ]

null

fhir/resources/tests/test_provenance.py

mmabey/fhir.resources

cc73718e9762c04726cd7de240c8f2dd5313cbe1

[ "BSD-3-Clause" ]

null

fhir/resources/tests/test_provenance.py

mmabey/fhir.resources

cc73718e9762c04726cd7de240c8f2dd5313cbe1

[ "BSD-3-Clause" ]

null

# -*- coding: utf-8 -*- """ Profile: http://hl7.org/fhir/StructureDefinition/Provenance Release: R4 Version: 4.0.1 Build ID: 9346c8cc45 Last updated: 2019-11-01T09:29:23.356+11:00 """ import io import json import os import unittest import pytest from .. import provenance from ..fhirdate import FHIRDate from .fixtures import force_bytes @pytest.mark.usefixtures("base_settings") class ProvenanceTests(unittest.TestCase): def instantiate_from(self, filename): datadir = os.environ.get("FHIR_UNITTEST_DATADIR") or "" with io.open(os.path.join(datadir, filename), "r", encoding="utf-8") as handle: js = json.load(handle) self.assertEqual("Provenance", js["resourceType"]) return provenance.Provenance(js) def testProvenance1(self): inst = self.instantiate_from("provenance-example-sig.json") self.assertIsNotNone(inst, "Must have instantiated a Provenance instance") self.implProvenance1(inst) js = inst.as_json() self.assertEqual("Provenance", js["resourceType"]) inst2 = provenance.Provenance(js) self.implProvenance1(inst2) def implProvenance1(self, inst): self.assertEqual(force_bytes(inst.activity.coding[0].code), force_bytes("AU")) self.assertEqual( force_bytes(inst.activity.coding[0].display), force_bytes("authenticated") ) self.assertEqual( force_bytes(inst.activity.coding[0].system), force_bytes("http://terminology.hl7.org/CodeSystem/v3-DocumentCompletion"), ) self.assertEqual( force_bytes(inst.agent[0].type.coding[0].code), force_bytes("VERF") ) self.assertEqual( force_bytes(inst.agent[0].type.coding[0].system), force_bytes( "http://terminology.hl7.org/CodeSystem/contractsignertypecodes" ), ) self.assertEqual(force_bytes(inst.id), force_bytes("signature")) self.assertEqual(force_bytes(inst.meta.tag[0].code), force_bytes("HTEST")) self.assertEqual( force_bytes(inst.meta.tag[0].display), force_bytes("test health data") ) self.assertEqual( force_bytes(inst.meta.tag[0].system), force_bytes("http://terminology.hl7.org/CodeSystem/v3-ActReason"), ) self.assertEqual( force_bytes(inst.reason[0].coding[0].code), force_bytes("TREAT") ) self.assertEqual( force_bytes(inst.reason[0].coding[0].display), force_bytes("treatment") ) self.assertEqual( force_bytes(inst.reason[0].coding[0].system), force_bytes("http://terminology.hl7.org/CodeSystem/v3-ActReason"), ) self.assertEqual(inst.recorded.date, FHIRDate("2015-08-27T08:39:24+10:00").date) self.assertEqual(inst.recorded.as_json(), "2015-08-27T08:39:24+10:00") self.assertEqual(force_bytes(inst.signature[0].data), force_bytes("Li4u")) self.assertEqual( force_bytes(inst.signature[0].sigFormat), force_bytes("application/signature+xml"), ) self.assertEqual( force_bytes(inst.signature[0].targetFormat), force_bytes("application/fhir+xml"), ) self.assertEqual( force_bytes(inst.signature[0].type[0].code), force_bytes("1.2.840.10065.1.12.1.5"), ) self.assertEqual( force_bytes(inst.signature[0].type[0].display), force_bytes("Verification Signature"), ) self.assertEqual( force_bytes(inst.signature[0].type[0].system), force_bytes("urn:iso-astm:E1762-95:2013"), ) self.assertEqual( inst.signature[0].when.date, FHIRDate("2015-08-27T08:39:24+10:00").date ) self.assertEqual(inst.signature[0].when.as_json(), "2015-08-27T08:39:24+10:00") self.assertEqual( force_bytes(inst.text.div), force_bytes( '<div xmlns="http://www.w3.org/1999/xhtml">procedure record authored on 27-June 2015 by Harold Hippocrates, MD Content extracted from Referral received 26-June</div>' ), ) self.assertEqual(force_bytes(inst.text.status), force_bytes("generated")) def testProvenance2(self): inst = self.instantiate_from("provenance-consent-signature.json") self.assertIsNotNone(inst, "Must have instantiated a Provenance instance") self.implProvenance2(inst) js = inst.as_json() self.assertEqual("Provenance", js["resourceType"]) inst2 = provenance.Provenance(js) self.implProvenance2(inst2) def implProvenance2(self, inst): self.assertEqual( force_bytes(inst.agent[0].role[0].coding[0].code), force_bytes("AUT") ) self.assertEqual( force_bytes(inst.agent[0].role[0].coding[0].system), force_bytes("http://terminology.hl7.org/CodeSystem/v3-ParticipationType"), ) self.assertEqual(force_bytes(inst.id), force_bytes("consent-signature")) self.assertEqual(force_bytes(inst.meta.tag[0].code), force_bytes("HTEST")) self.assertEqual( force_bytes(inst.meta.tag[0].display), force_bytes("test health data") ) self.assertEqual( force_bytes(inst.meta.tag[0].system), force_bytes("http://terminology.hl7.org/CodeSystem/v3-ActReason"), ) self.assertEqual(inst.recorded.date, FHIRDate("2016-05-26T00:41:10-04:00").date) self.assertEqual(inst.recorded.as_json(), "2016-05-26T00:41:10-04:00") self.assertEqual( force_bytes(inst.signature[0].data), force_bytes("dGhpcyBibG9iIGlzIHNuaXBwZWQ="), ) self.assertEqual( force_bytes(inst.signature[0].sigFormat), force_bytes("application/signature+xml"), ) self.assertEqual( force_bytes(inst.signature[0].targetFormat), force_bytes("application/fhir+xml"), ) self.assertEqual( force_bytes(inst.signature[0].type[0].code), force_bytes("1.2.840.10065.1.12.1.1"), ) self.assertEqual( force_bytes(inst.signature[0].type[0].display), force_bytes("Author's Signature"), ) self.assertEqual( force_bytes(inst.signature[0].type[0].system), force_bytes("urn:iso-astm:E1762-95:2013"), ) self.assertEqual( inst.signature[0].when.date, FHIRDate("2016-05-26T00:41:10-04:00").date ) self.assertEqual(inst.signature[0].when.as_json(), "2016-05-26T00:41:10-04:00") self.assertEqual(force_bytes(inst.text.status), force_bytes("generated")) def testProvenance3(self): inst = self.instantiate_from("provenance-example-cwl.json") self.assertIsNotNone(inst, "Must have instantiated a Provenance instance") self.implProvenance3(inst) js = inst.as_json() self.assertEqual("Provenance", js["resourceType"]) inst2 = provenance.Provenance(js) self.implProvenance3(inst2) def implProvenance3(self, inst): self.assertEqual( force_bytes(inst.agent[0].type.coding[0].code), force_bytes("AUT") ) self.assertEqual( force_bytes(inst.agent[0].type.coding[0].system), force_bytes("http://terminology.hl7.org/CodeSystem/v3-ParticipationType"), ) self.assertEqual(force_bytes(inst.entity[0].role), force_bytes("source")) self.assertEqual(force_bytes(inst.id), force_bytes("example-cwl")) self.assertEqual(force_bytes(inst.meta.tag[0].code), force_bytes("HTEST")) self.assertEqual( force_bytes(inst.meta.tag[0].display), force_bytes("test health data") ) self.assertEqual( force_bytes(inst.meta.tag[0].system), force_bytes("http://terminology.hl7.org/CodeSystem/v3-ActReason"), ) self.assertEqual(inst.occurredPeriod.start.date, FHIRDate("2016-11-30").date) self.assertEqual(inst.occurredPeriod.start.as_json(), "2016-11-30") self.assertEqual( force_bytes(inst.reason[0].text), force_bytes( "profiling Short Tandem Repeats (STRs) from high throughput sequencing data." ), ) self.assertEqual(inst.recorded.date, FHIRDate("2016-12-01T08:12:14+10:00").date) self.assertEqual(inst.recorded.as_json(), "2016-12-01T08:12:14+10:00") self.assertEqual(force_bytes(inst.text.status), force_bytes("generated")) def testProvenance4(self): inst = self.instantiate_from("provenance-example-biocompute-object.json") self.assertIsNotNone(inst, "Must have instantiated a Provenance instance") self.implProvenance4(inst) js = inst.as_json() self.assertEqual("Provenance", js["resourceType"]) inst2 = provenance.Provenance(js) self.implProvenance4(inst2) def implProvenance4(self, inst): self.assertEqual( force_bytes(inst.agent[0].type.coding[0].code), force_bytes("AUT") ) self.assertEqual( force_bytes(inst.agent[0].type.coding[0].system), force_bytes("http://terminology.hl7.org/CodeSystem/v3-ParticipationType"), ) self.assertEqual(force_bytes(inst.entity[0].role), force_bytes("source")) self.assertEqual(force_bytes(inst.id), force_bytes("example-biocompute-object")) self.assertEqual(force_bytes(inst.meta.tag[0].code), force_bytes("HTEST")) self.assertEqual( force_bytes(inst.meta.tag[0].display), force_bytes("test health data") ) self.assertEqual( force_bytes(inst.meta.tag[0].system), force_bytes("http://terminology.hl7.org/CodeSystem/v3-ActReason"), ) self.assertEqual(inst.occurredPeriod.start.date, FHIRDate("2017-06-06").date) self.assertEqual(inst.occurredPeriod.start.as_json(), "2017-06-06") self.assertEqual( force_bytes(inst.reason[0].text), force_bytes("antiviral resistance detection"), ) self.assertEqual(inst.recorded.date, FHIRDate("2016-06-09T08:12:14+10:00").date) self.assertEqual(inst.recorded.as_json(), "2016-06-09T08:12:14+10:00") self.assertEqual(force_bytes(inst.text.status), force_bytes("generated")) def testProvenance5(self): inst = self.instantiate_from("provenance-example.json") self.assertIsNotNone(inst, "Must have instantiated a Provenance instance") self.implProvenance5(inst) js = inst.as_json() self.assertEqual("Provenance", js["resourceType"]) inst2 = provenance.Provenance(js) self.implProvenance5(inst2) def implProvenance5(self, inst): self.assertEqual( force_bytes(inst.agent[0].type.coding[0].code), force_bytes("AUT") ) self.assertEqual( force_bytes(inst.agent[0].type.coding[0].system), force_bytes("http://terminology.hl7.org/CodeSystem/v3-ParticipationType"), ) self.assertEqual(force_bytes(inst.agent[1].id), force_bytes("a1")) self.assertEqual( force_bytes(inst.agent[1].type.coding[0].code), force_bytes("DEV") ) self.assertEqual( force_bytes(inst.agent[1].type.coding[0].system), force_bytes("http://terminology.hl7.org/CodeSystem/v3-ParticipationType"), ) self.assertEqual(force_bytes(inst.entity[0].role), force_bytes("source")) self.assertEqual(force_bytes(inst.id), force_bytes("example")) self.assertEqual(force_bytes(inst.meta.tag[0].code), force_bytes("HTEST")) self.assertEqual( force_bytes(inst.meta.tag[0].display), force_bytes("test health data") ) self.assertEqual( force_bytes(inst.meta.tag[0].system), force_bytes("http://terminology.hl7.org/CodeSystem/v3-ActReason"), ) self.assertEqual(inst.occurredPeriod.end.date, FHIRDate("2015-06-28").date) self.assertEqual(inst.occurredPeriod.end.as_json(), "2015-06-28") self.assertEqual(inst.occurredPeriod.start.date, FHIRDate("2015-06-27").date) self.assertEqual(inst.occurredPeriod.start.as_json(), "2015-06-27") self.assertEqual( force_bytes(inst.policy[0]), force_bytes("http://acme.com/fhir/Consent/25") ) self.assertEqual( force_bytes(inst.reason[0].coding[0].code), force_bytes("3457005") ) self.assertEqual( force_bytes(inst.reason[0].coding[0].display), force_bytes("Referral") ) self.assertEqual( force_bytes(inst.reason[0].coding[0].system), force_bytes("http://snomed.info/sct"), ) self.assertEqual(inst.recorded.date, FHIRDate("2015-06-27T08:39:24+10:00").date) self.assertEqual(inst.recorded.as_json(), "2015-06-27T08:39:24+10:00") self.assertEqual(force_bytes(inst.text.status), force_bytes("generated"))

43.176471

182

0.633212

1,556

13,212

5.275064

0.134961

0.162037

0.160819

0.201023

0.825902

0.808601

0.802388

0.753533

0.714303

0.712354

0

0.05522

0.22419

13,212

305

183

43.318033

0.745561

0.01317

0

0.487365

0

0.00361

0.196853

0.055334

0

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1

0.039711

false

0

0.028881

0

0.075812

0

null

0

1

0

null

0

7

1fbeaa6d6532947e5bc0d7f62851fee6d323dea1

135

py

Python

src/friendly_matrix/__init__.py

AitanG/numpy-string-indexed

cc2482118c3e7a6e15dff0c7a29ccc0fc245b6ae

[ "MIT" ]

null

src/friendly_matrix/__init__.py

AitanG/numpy-string-indexed

cc2482118c3e7a6e15dff0c7a29ccc0fc245b6ae

[ "MIT" ]

null

src/friendly_matrix/__init__.py

AitanG/numpy-string-indexed

cc2482118c3e7a6e15dff0c7a29ccc0fc245b6ae

[ "MIT" ]

null

from .friendly_matrix import * from .compute_matrix import * from .formatting import * from .methods import * from .operations import *

27

30

0.785185

17

135

6.117647

0.470588

0.384615

0.307692

0

0.140741

135

5

31

27

0.896552

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

1f34a2b63d85fcde3157e1afb0b0997c6ba104b7

5,554

py

Python

garecovery/tests/test_prompt.py

LeoComandini/garecovery

66f7fe4c15b3866e751162fd990bd5bc8c58ec7a

[ "MIT" ]

61

2017-08-30T13:16:42.000Z

2022-03-24T16:28:18.000Z

garecovery/tests/test_prompt.py

johnmahlon/garecovery

62aeb66e3fa674843c19a81c45e2ca35a693df97

[ "MIT" ]

34

2017-08-11T16:58:16.000Z

2022-02-18T09:00:23.000Z

garecovery/tests/test_prompt.py

johnmahlon/garecovery

62aeb66e3fa674843c19a81c45e2ca35a693df97

[ "MIT" ]

46

2017-08-09T18:11:55.000Z

2022-03-04T05:30:54.000Z

#!/usr/bin/env python3 import mock import garecovery.recoverycli from garecovery.clargs import DEFAULT_SUBACCOUNT_SEARCH_DEPTH from .util import AuthServiceProxy, datafile, get_output, raise_IOError garecovery.bitcoin_config.open = raise_IOError sub_depth = DEFAULT_SUBACCOUNT_SEARCH_DEPTH key_depth = 20 destination_address = 'mynHfTyTWyGGB76NBFbfUrTnn8YWQkTJVs' def test_mnemonic_prompt(): """Check if --mnemonic-file not passed mnemonic is via prompt""" with mock.patch('garecovery.recoverycli.user_input') as user_input_: mnemonic = open(datafile('mnemonic_1.txt')).read() mnemonic = ' '.join(mnemonic.split()) user_input_.return_value = mnemonic output = get_output([ '2of2', '--network=testnet', '--nlocktime-file={}'.format(datafile('compressed_1.zip')), ]) user_input_.assert_called_once_with('mnemonic/hex seed: ') tx, private_key_wif = output.split() assert tx == open(datafile("signed_2of2_1")).read().strip() assert private_key_wif == 'cNVkei2ZVzQLGNTeewPoRZ1hh1jGdt8M5b1GgcJDtWDm1bjjL4Kk' def test_hex_seed_prompt(): """Test passing hex seed via prompt""" with mock.patch('garecovery.recoverycli.user_input') as user_input_: mnemonic = open(datafile('hex_seed_1.txt')).read() mnemonic = ' '.join(mnemonic.split()) user_input_.return_value = mnemonic output = get_output([ '2of2', '--nlocktime-file={}'.format(datafile('compressed_1.zip')), ]) user_input_.assert_called_once_with('mnemonic/hex seed: ') tx, private_key_wif = output.split() assert tx == open(datafile("signed_2of2_1")).read().strip() assert private_key_wif == open(datafile("private_key_wif_1")).read().strip() @mock.patch('garecovery.two_of_three.bitcoincore.AuthServiceProxy') def test_prompt_for_mnemonic(mock_bitcoincore): """Test prompting for mnemonic""" mock_bitcoincore.return_value = AuthServiceProxy('testnet_txs') estimate = {'blocks': 3, 'feerate': 1, } mock_bitcoincore.return_value.estimatesmartfee.return_value = estimate with mock.patch('garecovery.recoverycli.user_input') as user_input_: mnemonic = open(datafile('mnemonic_6.txt')).read().strip() mnemonic = ' '.join(mnemonic.split()) user_input_.return_value = mnemonic output = get_output([ '--rpcuser=abc', '--rpcpassword=abc', '2of3', '--network=testnet', '--recovery-mnemonic-file={}'.format(datafile('mnemonic_7.txt')), '--key-search-depth={}'.format(key_depth), '--search-subaccounts={}'.format(sub_depth), '--destination-address={}'.format(destination_address), ]) user_input_.assert_called_once_with('mnemonic/hex seed: ') assert output.strip() == open(datafile("signed_2of3_5")).read().strip() sub_depth = garecovery.clargs.DEFAULT_SUBACCOUNT_SEARCH_DEPTH key_depth = 20 @mock.patch('garecovery.two_of_three.bitcoincore.AuthServiceProxy') def test_prompt_for_recovery_mnemonic(mock_bitcoincore): """Test prompting for recovery mnemonic""" mock_bitcoincore.return_value = AuthServiceProxy('testnet_txs') estimate = {'blocks': 3, 'feerate': 1, } mock_bitcoincore.return_value.estimatesmartfee.return_value = estimate with mock.patch('garecovery.recoverycli.user_input') as user_input_: recovery_mnemonic = open(datafile('mnemonic_7.txt')).read() recovery_mnemonic = ' '.join(recovery_mnemonic.split()) user_input_.return_value = recovery_mnemonic output = get_output([ '--mnemonic-file={}'.format(datafile('mnemonic_6.txt')), '--rpcuser=abc', '--rpcpassword=abc', '2of3', '--network=testnet', '--search-subaccounts={}'.format(sub_depth), '--key-search-depth={}'.format(key_depth), '--destination-address={}'.format(destination_address), ]) user_input_.assert_called_once_with('recovery mnemonic/hex seed: ') assert output.strip() == open(datafile("signed_2of3_5")).read().strip() @mock.patch('garecovery.two_of_three.bitcoincore.AuthServiceProxy') def test_prompt_for_both_mnemonics(mock_bitcoincore): """Test prompting for both mnemonic and recovery mnemonic""" mock_bitcoincore.return_value = AuthServiceProxy('testnet_txs') estimate = {'blocks': 3, 'feerate': 1, } mock_bitcoincore.return_value.estimatesmartfee.return_value = estimate with mock.patch('garecovery.recoverycli.user_input') as user_input_: mnemonic = open(datafile('mnemonic_6.txt')).read() mnemonic = ' '.join(mnemonic.split()) recovery_mnemonic = open(datafile('mnemonic_7.txt')).read() recovery_mnemonic = ' '.join(recovery_mnemonic.split()) user_input_.side_effect = (mnemonic, recovery_mnemonic) output = get_output([ '--rpcuser=abc', '--rpcpassword=abc', '2of3', '--network=testnet', '--key-search-depth={}'.format(key_depth), '--search-subaccounts={}'.format(sub_depth), '--destination-address={}'.format(destination_address), ]) user_input_.assert_has_calls([ mock.call('mnemonic/hex seed: '), mock.call('recovery mnemonic/hex seed: '), ]) assert output.strip() == open(datafile("signed_2of3_5")).read().strip()

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0.830998

0.780383

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0.013066

0.200756

5,554

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0.774724

0.041952

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0.740385

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0.028846

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1

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1f6d3a239256c036867ba14106415cf707293aae

121,714

py

Python

test/test_data_threathunter.py

JustinJohnWilliams/cbc-syslog

dae4b024214afae18328ee6c000db6312bf49d6d

[ "MIT" ]

null

test/test_data_threathunter.py

JustinJohnWilliams/cbc-syslog

dae4b024214afae18328ee6c000db6312bf49d6d

[ "MIT" ]

null

test/test_data_threathunter.py

JustinJohnWilliams/cbc-syslog

dae4b024214afae18328ee6c000db6312bf49d6d

[ "MIT" ]

null

# -*- coding: utf-8 -*- null = "" true = "true" false = "false" test_data_threat_hunter={ "notifications": [ { "threatHunterInfo": { "incidentId": "WNEXFKQ7-000049d4-00001ef0-00000000-1d4ed58a5f07dbf-j0MkcneCQXy1fIbhber6rw-565660", "score": 1, "summary": "PowerShell - File and Directory Discovery Enumeration", "time": 1554652050250, "indicators": [ { "applicationName": "powershell.exe", "sha256Hash": "ba4038fd20e474c047be8aad5bfacdb1bfc1ddbe12f803f473b7918d8d819436", "indicatorName": "565660-0" } ], "watchLists": [ { "id": "a3xW2ZiaRyAqRtuVES8Q", "name": "ATT&CK Framework", "alert": true } ], "iocId": "565660-0", "count": 0, "dismissed": false, "documentGuid": "7a9fQEsTRfuFmXcogI8CMQ", "firstActivityTime": 1554651811577, "md5": "097ce5761c89434367598b34fe32893b", "policyId": 9815, "processGuid": "WNEXFKQ7-000049d4-00001ef0-00000000-1d4ed58a5f07dbf", "processPath": "c:\\windows\\system32\\windowspowershell\\v1.0\\powershell.exe", "reportName": "PowerShell - File and Directory Discovery Enumeration", "reportId": "j0MkcneCQXy1fIbhber6rw-565660", "reputation": "TRUSTED_WHITE_LIST", "responseAlarmId": "WNEXFKQ7-000049d4-00001ef0-00000000-1d4ed58a5f07dbf-j0MkcneCQXy1fIbhber6rw-565660", "responseSeverity": 1, "runState": "RAN", "sha256": "ba4038fd20e474c047be8aad5bfacdb1bfc1ddbe12f803f473b7918d8d819436", "status": "UNRESOLVED", "tags": null, "targetPriority": "MEDIUM", "threatCause": { "reputation": "TRUSTED_WHITE_LIST", "actor": "ba4038fd20e474c047be8aad5bfacdb1bfc1ddbe12f803f473b7918d8d819436", "actorName": "powershell.exe", "reason": "Process powershell.exe was detected by the report \"PowerShell - File and Directory Discovery Enumeration\" in watchlist \"ATT&CK Framework\"", "actorType": null, "threatCategory": "RESPONSE_WATCHLIST", "actorProcessPPid": null, "causeEventId": null, "originSourceType": "UNKNOWN" }, "threatId": "a2b724aa094af97c06c758d325240460", "lastUpdatedTime": 0, "orgId": 428 }, "eventDescription": "[sm-sentinel-notification] [Carbon Black has detected a threat against your company.] [https://defense-eap01.conferdeploy.net#device/18900/incident/WNEXFKQ7-000049d4-00001ef0-00000000-1d4ed58a5f07dbf-j0MkcneCQXy1fIbhber6rw-565660] [PowerShell - File and Directory Discovery Enumeration] [Incident id: WNEXFKQ7-000049d4-00001ef0-00000000-1d4ed58a5f07dbf-j0MkcneCQXy1fIbhber6rw-565660] [Threat score: 1] [Group: sm-detection] [Email: smultani@carbonblack.com] [Name: win-559j1nqvfgj] [Type and OS: WINDOWS pscr-sensor] [Severity: 1]\n", "eventTime": 1554651811577, "deviceInfo": { "deviceId": 18900, "targetPriorityCode": 0, "groupName": "sm-detection", "deviceName": "win-559j1nqvfgj", "deviceType": "WINDOWS", "email": "smultani@carbonblack.com", "deviceHostName": null, "deviceVersion": "pscr-sensor", "targetPriorityType": "MEDIUM", "uemId": null, "internalIpAddress": "192.168.81.148", "externalIpAddress": "73.69.152.214" }, "url": "https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-00001ef0-00000000-1d4ed58a5f07dbf-j0MkcneCQXy1fIbhber6rw-565660", "ruleName": "sm-sentinel-notification", "type": "THREAT_HUNTER" }, { "threatHunterInfo": { "incidentId": "WNEXFKQ7-000049d4-00001ef0-00000000-1d4ed58a5f07dbf-j0MkcneCQXy1fIbhber6rw-565660", "score": 1, "summary": "PowerShell - File and Directory Discovery Enumeration", "time": 1554652050260, "indicators": [ { "applicationName": "powershell.exe", "sha256Hash": "ba4038fd20e474c047be8aad5bfacdb1bfc1ddbe12f803f473b7918d8d819436", "indicatorName": "565660-0" } ], "watchLists": [ { "id": "a3xW2ZiaRyAqRtuVES8Q", "name": "ATT&CK Framework", "alert": true } ], "iocId": "565660-0", "count": 0, "dismissed": false, "documentGuid": "7a9fQEsTRfuFmXcogI8CMQ", "firstActivityTime": 1554651811577, "md5": "097ce5761c89434367598b34fe32893b", "policyId": 9815, "processGuid": "WNEXFKQ7-000049d4-00001ef0-00000000-1d4ed58a5f07dbf", "processPath": "c:\\windows\\system32\\windowspowershell\\v1.0\\powershell.exe", "reportName": "PowerShell - File and Directory Discovery Enumeration", "reportId": "j0MkcneCQXy1fIbhber6rw-565660", "reputation": "TRUSTED_WHITE_LIST", "responseAlarmId": "WNEXFKQ7-000049d4-00001ef0-00000000-1d4ed58a5f07dbf-j0MkcneCQXy1fIbhber6rw-565660", "responseSeverity": 1, "runState": "RAN", "sha256": "ba4038fd20e474c047be8aad5bfacdb1bfc1ddbe12f803f473b7918d8d819436", "status": "UNRESOLVED", "tags": null, "targetPriority": "MEDIUM", "threatCause": { "reputation": "TRUSTED_WHITE_LIST", "actor": "ba4038fd20e474c047be8aad5bfacdb1bfc1ddbe12f803f473b7918d8d819436", "actorName": "powershell.exe", "reason": "Process powershell.exe was detected by the report \"PowerShell - File and Directory Discovery Enumeration\" in watchlist \"ATT&CK Framework\"", "actorType": null, "threatCategory": "RESPONSE_WATCHLIST", "actorProcessPPid": null, "causeEventId": null, "originSourceType": "UNKNOWN" }, "threatId": "a2b724aa094af97c06c758d325240460", "lastUpdatedTime": 0, "orgId": 428 }, "eventDescription": "[sm-sentinel-watchlist] [Carbon Black has detected one or more threat indicator(s) on one of your devices.] [https://defense-eap01.conferdeploy.net/threat-hunter/analyze?processGUID=WNEXFKQ7-000049d4-00001ef0-00000000-1d4ed58a5f07dbf&deviceId=18900] [PowerShell - File and Directory Discovery Enumeration] [Group: sm-detection] [Device Email: smultani@carbonblack.com] [Device Name: win-559j1nqvfgj] [Device Type: WINDOWS] [IOC: 565660-0] [Severity: 1]", "eventTime": 1554651811577, "deviceInfo": { "deviceId": 18900, "targetPriorityCode": 0, "groupName": "sm-detection", "deviceName": "win-559j1nqvfgj", "deviceType": "WINDOWS", "email": "smultani@carbonblack.com", "deviceHostName": null, "deviceVersion": "pscr-sensor", "targetPriorityType": "MEDIUM", "uemId": null, "internalIpAddress": "192.168.81.148", "externalIpAddress": "73.69.152.214" }, "url": "https://defense-eap01.conferdeploy.net", "ruleName": "sm-sentinel-watchlist", "type": "THREAT_HUNTER" }, { "threatHunterInfo": { "incidentId": "WNEXFKQ7-000049d4-000013d8-00000000-1d4ed587c0142d0-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507", "score": 10, "summary": "T1003 - Credential Dumping #2", "time": 1554652058988, "indicators": [ { "applicationName": "mimikatz.exe", "sha256Hash": "6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be", "indicatorName": "b7e9fd8e-febe-478c-8f44-2e90e0d10507-0" } ], "watchLists": [ { "id": "3ExgIixySwmbRuaXoxxKeA", "name": "Carbon Black Advanced Threats", "alert": true } ], "iocId": "b7e9fd8e-febe-478c-8f44-2e90e0d10507-0", "count": 0, "dismissed": false, "documentGuid": "NoKzSz7wTzSil0ur7wYG0Q", "firstActivityTime": 1554651774855, "md5": "9e9ea5e8a16995124ba6e75bad4c6abe", "policyId": 9815, "processGuid": "WNEXFKQ7-000049d4-000013d8-00000000-1d4ed587c0142d0", "processPath": "c:\\users\\smultani\\music\\mimikatz_trunk (1)\\win32\\mimikatz.exe", "reportName": "T1003 - Credential Dumping #2", "reportId": "1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507", "reputation": "KNOWN_MALWARE", "responseAlarmId": "WNEXFKQ7-000049d4-000013d8-00000000-1d4ed587c0142d0-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507", "responseSeverity": 10, "runState": "RAN", "sha256": "6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be", "status": "UNRESOLVED", "tags": null, "targetPriority": "MEDIUM", "threatCause": { "reputation": "KNOWN_MALWARE", "actor": "6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be", "actorName": "mimikatz.exe", "reason": "Process mimikatz.exe was detected by the report \"T1003 - Credential Dumping #2\" in watchlist \"Carbon Black Advanced Threats\"", "actorType": null, "threatCategory": "RESPONSE_WATCHLIST", "actorProcessPPid": null, "causeEventId": null, "originSourceType": "UNKNOWN" }, "threatId": "5f1763e2ea26c424e8a84ec6b1090983", "lastUpdatedTime": 0, "orgId": 428 }, "eventDescription": "[sm-sentinel-notification] [Carbon Black has detected a threat against your company.] [https://defense-eap01.conferdeploy.net#device/18900/incident/WNEXFKQ7-000049d4-000013d8-00000000-1d4ed587c0142d0-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507] [T1003 - Credential Dumping #2] [Incident id: WNEXFKQ7-000049d4-000013d8-00000000-1d4ed587c0142d0-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507] [Threat score: 10] [Group: sm-detection] [Email: smultani@carbonblack.com] [Name: win-559j1nqvfgj] [Type and OS: WINDOWS pscr-sensor] [Severity: 10]\n", "eventTime": 1554651774855, "deviceInfo": { "deviceId": 18900, "targetPriorityCode": 0, "groupName": "sm-detection", "deviceName": "win-559j1nqvfgj", "deviceType": "WINDOWS", "email": "smultani@carbonblack.com", "deviceHostName": null, "deviceVersion": "pscr-sensor", "targetPriorityType": "MEDIUM", "uemId": null, "internalIpAddress": "192.168.81.148", "externalIpAddress": "73.69.152.214" }, "url": "https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-000013d8-00000000-1d4ed587c0142d0-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507", "ruleName": "sm-sentinel-notification", "type": "THREAT_HUNTER" }, { "threatHunterInfo": { "incidentId": "WNEXFKQ7-000049d4-000013d8-00000000-1d4ed587c0142d0-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507", "score": 10, "summary": "T1003 - Credential Dumping #2", "time": 1554652058999, "indicators": [ { "applicationName": "mimikatz.exe", "sha256Hash": "6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be", "indicatorName": "b7e9fd8e-febe-478c-8f44-2e90e0d10507-0" } ], "watchLists": [ { "id": "3ExgIixySwmbRuaXoxxKeA", "name": "Carbon Black Advanced Threats", "alert": true } ], "iocId": "b7e9fd8e-febe-478c-8f44-2e90e0d10507-0", "count": 0, "dismissed": false, "documentGuid": "NoKzSz7wTzSil0ur7wYG0Q", "firstActivityTime": 1554651774855, "md5": "9e9ea5e8a16995124ba6e75bad4c6abe", "policyId": 9815, "processGuid": "WNEXFKQ7-000049d4-000013d8-00000000-1d4ed587c0142d0", "processPath": "c:\\users\\smultani\\music\\mimikatz_trunk (1)\\win32\\mimikatz.exe", "reportName": "T1003 - Credential Dumping #2", "reportId": "1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507", "reputation": "KNOWN_MALWARE", "responseAlarmId": "WNEXFKQ7-000049d4-000013d8-00000000-1d4ed587c0142d0-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507", "responseSeverity": 10, "runState": "RAN", "sha256": "6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be", "status": "UNRESOLVED", "tags": null, "targetPriority": "MEDIUM", "threatCause": { "reputation": "KNOWN_MALWARE", "actor": "6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be", "actorName": "mimikatz.exe", "reason": "Process mimikatz.exe was detected by the report \"T1003 - Credential Dumping #2\" in watchlist \"Carbon Black Advanced Threats\"", "actorType": null, "threatCategory": "RESPONSE_WATCHLIST", "actorProcessPPid": null, "causeEventId": null, "originSourceType": "UNKNOWN" }, "threatId": "5f1763e2ea26c424e8a84ec6b1090983", "lastUpdatedTime": 0, "orgId": 428 }, "eventDescription": "[sm-sentinel-watchlist] [Carbon Black has detected one or more threat indicator(s) on one of your devices.] [https://defense-eap01.conferdeploy.net/threat-hunter/analyze?processGUID=WNEXFKQ7-000049d4-000013d8-00000000-1d4ed587c0142d0&deviceId=18900] [T1003 - Credential Dumping #2] [Group: sm-detection] [Device Email: smultani@carbonblack.com] [Device Name: win-559j1nqvfgj] [Device Type: WINDOWS] [IOC: b7e9fd8e-febe-478c-8f44-2e90e0d10507-0] [Severity: 10]", "eventTime": 1554651774855, "deviceInfo": { "deviceId": 18900, "targetPriorityCode": 0, "groupName": "sm-detection", "deviceName": "win-559j1nqvfgj", "deviceType": "WINDOWS", "email": "smultani@carbonblack.com", "deviceHostName": null, "deviceVersion": "pscr-sensor", "targetPriorityType": "MEDIUM", "uemId": null, "internalIpAddress": "192.168.81.148", "externalIpAddress": "73.69.152.214" }, "url": "https://defense-eap01.conferdeploy.net", "ruleName": "sm-sentinel-watchlist", "type": "THREAT_HUNTER" }, { "threatHunterInfo": { "incidentId": "WNEXFKQ7-000049d4-00000954-00000000-1d4ed5809bf5af8-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507", "score": 10, "summary": "T1003 - Credential Dumping #2", "time": 1554652062174, "indicators": [ { "applicationName": "mimikatz.exe", "sha256Hash": "6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be", "indicatorName": "b7e9fd8e-febe-478c-8f44-2e90e0d10507-0" } ], "watchLists": [ { "id": "3ExgIixySwmbRuaXoxxKeA", "name": "Carbon Black Advanced Threats", "alert": true } ], "iocId": "b7e9fd8e-febe-478c-8f44-2e90e0d10507-0", "count": 0, "dismissed": false, "documentGuid": "F-OinTckReGkfHVvNZqe1w", "firstActivityTime": 1554651550298, "md5": "9e9ea5e8a16995124ba6e75bad4c6abe", "policyId": 9815, "processGuid": "WNEXFKQ7-000049d4-00000954-00000000-1d4ed5809bf5af8", "processPath": "c:\\users\\smultani\\desktop\\mimikatz_trunk (1)\\win32\\mimikatz.exe", "reportName": "T1003 - Credential Dumping #2", "reportId": "1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507", "reputation": "KNOWN_MALWARE", "responseAlarmId": "WNEXFKQ7-000049d4-00000954-00000000-1d4ed5809bf5af8-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507", "responseSeverity": 10, "runState": "RAN", "sha256": "6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be", "status": "UNRESOLVED", "tags": null, "targetPriority": "MEDIUM", "threatCause": { "reputation": "KNOWN_MALWARE", "actor": "6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be", "actorName": "mimikatz.exe", "reason": "Process mimikatz.exe was detected by the report \"T1003 - Credential Dumping #2\" in watchlist \"Carbon Black Advanced Threats\"", "actorType": null, "threatCategory": "RESPONSE_WATCHLIST", "actorProcessPPid": null, "causeEventId": null, "originSourceType": "UNKNOWN" }, "threatId": "5f1763e2ea26c424e8a84ec6b1090983", "lastUpdatedTime": 0, "orgId": 428 }, "eventDescription": "[sm-sentinel-watchlist] [Carbon Black has detected one or more threat indicator(s) on one of your devices.] [https://defense-eap01.conferdeploy.net/threat-hunter/analyze?processGUID=WNEXFKQ7-000049d4-00000954-00000000-1d4ed5809bf5af8&deviceId=18900] [T1003 - Credential Dumping #2] [Group: sm-detection] [Device Email: smultani@carbonblack.com] [Device Name: win-559j1nqvfgj] [Device Type: WINDOWS] [IOC: b7e9fd8e-febe-478c-8f44-2e90e0d10507-0] [Severity: 10]", "eventTime": 1554651550298, "deviceInfo": { "deviceId": 18900, "targetPriorityCode": 0, "groupName": "sm-detection", "deviceName": "win-559j1nqvfgj", "deviceType": "WINDOWS", "email": "smultani@carbonblack.com", "deviceHostName": null, "deviceVersion": "pscr-sensor", "targetPriorityType": "MEDIUM", "uemId": null, "internalIpAddress": "192.168.81.148", "externalIpAddress": "73.69.152.214" }, "url": "https://defense-eap01.conferdeploy.net", "ruleName": "sm-sentinel-watchlist", "type": "THREAT_HUNTER" }, { "threatHunterInfo": { "incidentId": "WNEXFKQ7-000049d4-00001e18-00000000-1d4ed58784102f9-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507", "score": 10, "summary": "T1003 - Credential Dumping #2", "time": 1554652062191, "indicators": [ { "applicationName": "mimikatz.exe", "sha256Hash": "38ff9593dcd07b0252ed3f1ad34ce7b538c522fd2a4d6ffef00f73767e75edac", "indicatorName": "b7e9fd8e-febe-478c-8f44-2e90e0d10507-0" } ], "watchLists": [ { "id": "3ExgIixySwmbRuaXoxxKeA", "name": "Carbon Black Advanced Threats", "alert": true } ], "iocId": "b7e9fd8e-febe-478c-8f44-2e90e0d10507-0", "count": 0, "dismissed": false, "documentGuid": "qgp18td2TFK2Dw3YB2MuSA", "firstActivityTime": 1554651734686, "md5": "a3298b7614ff07f91301655edd58e9d7", "policyId": 9815, "processGuid": "WNEXFKQ7-000049d4-00001e18-00000000-1d4ed58784102f9", "processPath":"c:\\users\\smultani\\music\\mimikatz_trunk (1)\d\\mimikatz.exe", "reportName": "T1003 - Credential Dumping #2", "reportId": "1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507", "reputation": "PUP", "responseAlarmId": "WNEXFKQ7-000049d4-00001e18-00000000-1d4ed58784102f9-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507", "responseSeverity": 10, "runState": "RAN", "sha256": "38ff9593dcd07b0252ed3f1ad34ce7b538c522fd2a4d6ffef00f73767e75edac", "status": "UNRESOLVED", "tags": null, "targetPriority": "MEDIUM", "threatCause": { "reputation": "PUP", "actor": "38ff9593dcd07b0252ed3f1ad34ce7b538c522fd2a4d6ffef00f73767e75edac", "actorName": "mimikatz.exe", "reason": "Process mimikatz.exe was detected by the report \"T1003 - Credential Dumping #2\" in watchlist \"Carbon Black Advanced Threats\"", "actorType": null, "threatCategory": "RESPONSE_WATCHLIST", "actorProcessPPid": null, "causeEventId": null, "originSourceType": "UNKNOWN" }, "threatId": "5f1763e2ea26c424e8a84ec6b1090983", "lastUpdatedTime": 0, "orgId": 428 }, "eventDescription": "[sm-sentinel-notification] [Carbon Black has detected a threat against your company.] [https://defense-eap01.conferdeploy.net#device/18900/incident/WNEXFKQ7-000049d4-00001e18-00000000-1d4ed58784102f9-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507] [T1003 - Credential Dumping #2] [Incident id: WNEXFKQ7-000049d4-00001e18-00000000-1d4ed58784102f9-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507] [Threat score: 10] [Group: sm-detection] [Email: smultani@carbonblack.com] [Name: win-559j1nqvfgj] [Type and OS: WINDOWS pscr-sensor] [Severity: 10]\n", "eventTime": 1554651734686, "deviceInfo": { "deviceId": 18900, "targetPriorityCode": 0, "groupName": "sm-detection", "deviceName": "win-559j1nqvfgj", "deviceType": "WINDOWS", "email": "smultani@carbonblack.com", "deviceHostName": null, "deviceVersion": "pscr-sensor", "targetPriorityType": "MEDIUM", "uemId": null, "internalIpAddress": "192.168.81.148", "externalIpAddress": "73.69.152.214" }, "url": "https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-00001e18-00000000-1d4ed58784102f9-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507", "ruleName": "sm-sentinel-notification", "type": "THREAT_HUNTER" }, { "threatHunterInfo": { "incidentId": "WNEXFKQ7-000049d4-00001e18-00000000-1d4ed58784102f9-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507", "score": 10, "summary": "T1003 - Credential Dumping #2", "time": 1554652062248, "indicators": [ { "applicationName": "mimikatz.exe", "sha256Hash": "38ff9593dcd07b0252ed3f1ad34ce7b538c522fd2a4d6ffef00f73767e75edac", "indicatorName": "b7e9fd8e-febe-478c-8f44-2e90e0d10507-0" } ], "watchLists": [ { "id": "3ExgIixySwmbRuaXoxxKeA", "name": "Carbon Black Advanced Threats", "alert": true } ], "iocId": "b7e9fd8e-febe-478c-8f44-2e90e0d10507-0", "count": 0, "dismissed": false, "documentGuid": "qgp18td2TFK2Dw3YB2MuSA", "firstActivityTime": 1554651734686, "md5": "a3298b7614ff07f91301655edd58e9d7", "policyId": 9815, "processGuid": "WNEXFKQ7-000049d4-00001e18-00000000-1d4ed58784102f9", "processPath":"c:\\users\\smultani\\music\\mimikatz_trunk (1)\d\\mimikatz.exe", "reportName": "T1003 - Credential Dumping #2", "reportId": "1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507", "reputation": "PUP", "responseAlarmId": "WNEXFKQ7-000049d4-00001e18-00000000-1d4ed58784102f9-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507", "responseSeverity": 10, "runState": "RAN", "sha256": "38ff9593dcd07b0252ed3f1ad34ce7b538c522fd2a4d6ffef00f73767e75edac", "status": "UNRESOLVED", "tags": null, "targetPriority": "MEDIUM", "threatCause": { "reputation": "PUP", "actor": "38ff9593dcd07b0252ed3f1ad34ce7b538c522fd2a4d6ffef00f73767e75edac", "actorName": "mimikatz.exe", "reason": "Process mimikatz.exe was detected by the report \"T1003 - Credential Dumping #2\" in watchlist \"Carbon Black Advanced Threats\"", "actorType": null, "threatCategory": "RESPONSE_WATCHLIST", "actorProcessPPid": null, "causeEventId": null, "originSourceType": "UNKNOWN" }, "threatId": "5f1763e2ea26c424e8a84ec6b1090983", "lastUpdatedTime": 0, "orgId": 428 }, "eventDescription": "[sm-sentinel-watchlist] [Carbon Black has detected one or more threat indicator(s) on one of your devices.] [https://defense-eap01.conferdeploy.net/threat-hunter/analyze?processGUID=WNEXFKQ7-000049d4-00001e18-00000000-1d4ed58784102f9&deviceId=18900] [T1003 - Credential Dumping #2] [Group: sm-detection] [Device Email: smultani@carbonblack.com] [Device Name: win-559j1nqvfgj] [Device Type: WINDOWS] [IOC: b7e9fd8e-febe-478c-8f44-2e90e0d10507-0] [Severity: 10]", "eventTime": 1554651734686, "deviceInfo": { "deviceId": 18900, "targetPriorityCode": 0, "groupName": "sm-detection", "deviceName": "win-559j1nqvfgj", "deviceType": "WINDOWS", "email": "smultani@carbonblack.com", "deviceHostName": null, "deviceVersion": "pscr-sensor", "targetPriorityType": "MEDIUM", "uemId": null, "internalIpAddress": "192.168.81.148", "externalIpAddress": "73.69.152.214" }, "url": "https://defense-eap01.conferdeploy.net", "ruleName": "sm-sentinel-watchlist", "type": "THREAT_HUNTER" }, { "threatHunterInfo": { "incidentId": "WNEXFKQ7-000049d4-00000954-00000000-1d4ed5809bf5af8-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507", "score": 10, "summary": "T1003 - Credential Dumping #2", "time": 1554652062265, "indicators": [ { "applicationName": "mimikatz.exe", "sha256Hash": "6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be", "indicatorName": "b7e9fd8e-febe-478c-8f44-2e90e0d10507-0" } ], "watchLists": [ { "id": "3ExgIixySwmbRuaXoxxKeA", "name": "Carbon Black Advanced Threats", "alert": true } ], "iocId": "b7e9fd8e-febe-478c-8f44-2e90e0d10507-0", "count": 0, "dismissed": false, "documentGuid": "F-OinTckReGkfHVvNZqe1w", "firstActivityTime": 1554651550298, "md5": "9e9ea5e8a16995124ba6e75bad4c6abe", "policyId": 9815, "processGuid": "WNEXFKQ7-000049d4-00000954-00000000-1d4ed5809bf5af8", "processPath": "c:\\users\\smultani\\desktop\\mimikatz_trunk (1)\\win32\\mimikatz.exe", "reportName": "T1003 - Credential Dumping #2", "reportId": "1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507", "reputation": "KNOWN_MALWARE", "responseAlarmId": "WNEXFKQ7-000049d4-00000954-00000000-1d4ed5809bf5af8-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507", "responseSeverity": 10, "runState": "RAN", "sha256": "6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be", "status": "UNRESOLVED", "tags": null, "targetPriority": "MEDIUM", "threatCause": { "reputation": "KNOWN_MALWARE", "actor": "6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be", "actorName": "mimikatz.exe", "reason": "Process mimikatz.exe was detected by the report \"T1003 - Credential Dumping #2\" in watchlist \"Carbon Black Advanced Threats\"", "actorType": null, "threatCategory": "RESPONSE_WATCHLIST", "actorProcessPPid": null, "causeEventId": null, "originSourceType": "UNKNOWN" }, "threatId": "5f1763e2ea26c424e8a84ec6b1090983", "lastUpdatedTime": 0, "orgId": 428 }, "eventDescription": "[sm-sentinel-notification] [Carbon Black has detected a threat against your company.] [https://defense-eap01.conferdeploy.net#device/18900/incident/WNEXFKQ7-000049d4-00000954-00000000-1d4ed5809bf5af8-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507] [T1003 - Credential Dumping #2] [Incident id: WNEXFKQ7-000049d4-00000954-00000000-1d4ed5809bf5af8-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507] [Threat score: 10] [Group: sm-detection] [Email: smultani@carbonblack.com] [Name: win-559j1nqvfgj] [Type and OS: WINDOWS pscr-sensor] [Severity: 10]\n", "eventTime": 1554651550298, "deviceInfo": { "deviceId": 18900, "targetPriorityCode": 0, "groupName": "sm-detection", "deviceName": "win-559j1nqvfgj", "deviceType": "WINDOWS", "email": "smultani@carbonblack.com", "deviceHostName": null, "deviceVersion": "pscr-sensor", "targetPriorityType": "MEDIUM", "uemId": null, "internalIpAddress": "192.168.81.148", "externalIpAddress": "73.69.152.214" }, "url": "https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-00000954-00000000-1d4ed5809bf5af8-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507", "ruleName": "sm-sentinel-notification", "type": "THREAT_HUNTER" }, { "threatHunterInfo": { "incidentId": "WNEXFKQ7-000049d4-00000ac8-00000000-1d4ed590863aac9-n8JQkq8TuqkYoTiT5wObg-47a50561-e6ff-4106-8df1-5777f70a98d5", "score": 9, "summary": "Memory Grab using ProcDump", "time": 1554652418230, "indicators": [ { "applicationName": "procdump64.exe", "sha256Hash": "16f413862efda3aba631d8a7ae2bfff6d84acd9f454a7adaa518c7a8a6f375a5", "indicatorName": "47a50561-e6ff-4106-8df1-5777f70a98d5-0" } ], "watchLists": [ { "id": "JBeEYzBcQpSMXu3lWoSv8w", "name": "Carbon Black Community", "alert": true } ], "iocId": "47a50561-e6ff-4106-8df1-5777f70a98d5-0", "count": 0, "dismissed": false, "documentGuid": "L8UMm1dOR76_T6nBv-PBFw", "firstActivityTime": 1554651976107, "md5": "a92669ec8852230a10256ac23bbf4489", "policyId": 9815, "processGuid": "WNEXFKQ7-000049d4-00000ac8-00000000-1d4ed590863aac9", "processPath": "c:\\users\\smultani\\downloads\\procdump\\procdump64.exe", "reportName": "Memory Grab using ProcDump", "reportId": "n8JQkq8TuqkYoTiT5wObg-47a50561-e6ff-4106-8df1-5777f70a98d5", "reputation": "TRUSTED_WHITE_LIST", "responseAlarmId": "WNEXFKQ7-000049d4-00000ac8-00000000-1d4ed590863aac9-n8JQkq8TuqkYoTiT5wObg-47a50561-e6ff-4106-8df1-5777f70a98d5", "responseSeverity": 9, "runState": "RAN", "sha256": "16f413862efda3aba631d8a7ae2bfff6d84acd9f454a7adaa518c7a8a6f375a5", "status": "UNRESOLVED", "tags": null, "targetPriority": "MEDIUM", "threatCause": { "reputation": "TRUSTED_WHITE_LIST", "actor": "16f413862efda3aba631d8a7ae2bfff6d84acd9f454a7adaa518c7a8a6f375a5", "actorName": "procdump64.exe", "reason": "Process procdump64.exe was detected by the report \"Memory Grab using ProcDump\" in watchlist \"Carbon Black Community\"", "actorType": null, "threatCategory": "RESPONSE_WATCHLIST", "actorProcessPPid": null, "causeEventId": null, "originSourceType": "UNKNOWN" }, "threatId": "db260acf65984a2c74ae0c41a8e08086", "lastUpdatedTime": 0, "orgId": 428 }, "eventDescription": "[sm-sentinel-notification] [Carbon Black has detected a threat against your company.] [https://defense-eap01.conferdeploy.net#device/18900/incident/WNEXFKQ7-000049d4-00000ac8-00000000-1d4ed590863aac9-n8JQkq8TuqkYoTiT5wObg-47a50561-e6ff-4106-8df1-5777f70a98d5] [Memory Grab using ProcDump] [Incident id: WNEXFKQ7-000049d4-00000ac8-00000000-1d4ed590863aac9-n8JQkq8TuqkYoTiT5wObg-47a50561-e6ff-4106-8df1-5777f70a98d5] [Threat score: 9] [Group: sm-detection] [Email: smultani@carbonblack.com] [Name: win-559j1nqvfgj] [Type and OS: WINDOWS pscr-sensor] [Severity: 9]\n", "eventTime": 1554651976107, "deviceInfo": { "deviceId": 18900, "targetPriorityCode": 0, "groupName": "sm-detection", "deviceName": "win-559j1nqvfgj", "deviceType": "WINDOWS", "email": "smultani@carbonblack.com", "deviceHostName": null, "deviceVersion": "pscr-sensor", "targetPriorityType": "MEDIUM", "uemId": null, "internalIpAddress": "192.168.81.148", "externalIpAddress": "73.69.152.214" }, "url": "https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-00000ac8-00000000-1d4ed590863aac9-n8JQkq8TuqkYoTiT5wObg-47a50561-e6ff-4106-8df1-5777f70a98d5", "ruleName": "sm-sentinel-notification", "type": "THREAT_HUNTER" }, { "threatHunterInfo": { "incidentId": "WNEXFKQ7-000049d4-000011c4-00000000-1d4ed58af5a4ce9-1X7Zx5ZRbGc24xRp7IaQ-7aa6e57a-6fa8-423d-b997-427565bf7a06", "score": 9, "summary": "T1003 - Credential Dumping #3", "time": 1554652418279, "indicators": [ { "applicationName": "procdump.exe", "sha256Hash": "05732e84de58a3cc142535431b3aa04efbe034cc96e837f93c360a6387d8faad", "indicatorName": "7aa6e57a-6fa8-423d-b997-427565bf7a06-0" } ], "watchLists": [ { "id": "3ExgIixySwmbRuaXoxxKeA", "name": "Carbon Black Advanced Threats", "alert": true } ], "iocId": "7aa6e57a-6fa8-423d-b997-427565bf7a06-0", "count": 0, "dismissed": false, "documentGuid": "NM1Pn_drQ3airxKooRokmQ", "firstActivityTime": 1554651828170, "md5": "6a09bc6c19c4236c0bd8a01953371a29", "policyId": 9815, "processGuid": "WNEXFKQ7-000049d4-000011c4-00000000-1d4ed58af5a4ce9", "processPath": "c:\\users\\smultani\\downloads\\procdump\\procdump.exe", "reportName": "T1003 - Credential Dumping #3", "reportId": "1X7Zx5ZRbGc24xRp7IaQ-7aa6e57a-6fa8-423d-b997-427565bf7a06", "reputation": "TRUSTED_WHITE_LIST", "responseAlarmId": "WNEXFKQ7-000049d4-000011c4-00000000-1d4ed58af5a4ce9-1X7Zx5ZRbGc24xRp7IaQ-7aa6e57a-6fa8-423d-b997-427565bf7a06", "responseSeverity": 9, "runState": "RAN", "sha256": "05732e84de58a3cc142535431b3aa04efbe034cc96e837f93c360a6387d8faad", "status": "UNRESOLVED", "tags": null, "targetPriority": "MEDIUM", "threatCause": { "reputation": "TRUSTED_WHITE_LIST", "actor": "05732e84de58a3cc142535431b3aa04efbe034cc96e837f93c360a6387d8faad", "actorName": "procdump.exe", "reason": "Process procdump.exe was detected by the report \"T1003 - Credential Dumping #3\" in watchlist \"Carbon Black Advanced Threats\"", "actorType": null, "threatCategory": "RESPONSE_WATCHLIST", "actorProcessPPid": null, "causeEventId": null, "originSourceType": "UNKNOWN" }, "threatId": "ddb41379ce092f02c635851f4a9364f2", "lastUpdatedTime": 0, "orgId": 428 }, "eventDescription": "[sm-sentinel-notification] [Carbon Black has detected a threat against your company.] [https://defense-eap01.conferdeploy.net#device/18900/incident/WNEXFKQ7-000049d4-000011c4-00000000-1d4ed58af5a4ce9-1X7Zx5ZRbGc24xRp7IaQ-7aa6e57a-6fa8-423d-b997-427565bf7a06] [T1003 - Credential Dumping #3] [Incident id: WNEXFKQ7-000049d4-000011c4-00000000-1d4ed58af5a4ce9-1X7Zx5ZRbGc24xRp7IaQ-7aa6e57a-6fa8-423d-b997-427565bf7a06] [Threat score: 9] [Group: sm-detection] [Email: smultani@carbonblack.com] [Name: win-559j1nqvfgj] [Type and OS: WINDOWS pscr-sensor] [Severity: 9]\n", "eventTime": 1554651828170, "deviceInfo": { "deviceId": 18900, "targetPriorityCode": 0, "groupName": "sm-detection", "deviceName": "win-559j1nqvfgj", "deviceType": "WINDOWS", "email": "smultani@carbonblack.com", "deviceHostName": null, "deviceVersion": "pscr-sensor", "targetPriorityType": "MEDIUM", "uemId": null, "internalIpAddress": "192.168.81.148", "externalIpAddress": "73.69.152.214" }, "url": "https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-000011c4-00000000-1d4ed58af5a4ce9-1X7Zx5ZRbGc24xRp7IaQ-7aa6e57a-6fa8-423d-b997-427565bf7a06", "ruleName": "sm-sentinel-notification", "type": "THREAT_HUNTER" }, { "threatHunterInfo": { "incidentId": "WNEXFKQ7-000049d4-00001228-00000000-1d4ed58b5502502-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507", "score": 10, "summary": "T1003 - Credential Dumping #2", "time": 1554652418305, "indicators": [ { "applicationName": "mimikatz.exe", "sha256Hash": "6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be", "indicatorName": "b7e9fd8e-febe-478c-8f44-2e90e0d10507-0" } ], "watchLists": [ { "id": "3ExgIixySwmbRuaXoxxKeA", "name": "Carbon Black Advanced Threats", "alert": true } ], "iocId": "b7e9fd8e-febe-478c-8f44-2e90e0d10507-0", "count": 0, "dismissed": false, "documentGuid": "FtA0ybjVRJuJ2VohA5E-Lw", "firstActivityTime": 1554651837865, "md5": "9e9ea5e8a16995124ba6e75bad4c6abe", "policyId": 9815, "processGuid": "WNEXFKQ7-000049d4-00001228-00000000-1d4ed58b5502502", "processPath": "c:\\users\\smultani\\music\\mimikatz_trunk (1)\\win32\\mimikatz.exe", "reportName": "T1003 - Credential Dumping #2", "reportId": "1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507", "reputation": "KNOWN_MALWARE", "responseAlarmId": "WNEXFKQ7-000049d4-00001228-00000000-1d4ed58b5502502-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507", "responseSeverity": 10, "runState": "RAN", "sha256": "6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be", "status": "UNRESOLVED", "tags": null, "targetPriority": "MEDIUM", "threatCause": { "reputation": "KNOWN_MALWARE", "actor": "6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be", "actorName": "mimikatz.exe", "reason": "Process mimikatz.exe was detected by the report \"T1003 - Credential Dumping #2\" in watchlist \"Carbon Black Advanced Threats\"", "actorType": null, "threatCategory": "RESPONSE_WATCHLIST", "actorProcessPPid": null, "causeEventId": null, "originSourceType": "UNKNOWN" }, "threatId": "5f1763e2ea26c424e8a84ec6b1090983", "lastUpdatedTime": 0, "orgId": 428 }, "eventDescription": "[sm-sentinel-notification] [Carbon Black has detected a threat against your company.] [https://defense-eap01.conferdeploy.net#device/18900/incident/WNEXFKQ7-000049d4-00001228-00000000-1d4ed58b5502502-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507] [T1003 - Credential Dumping #2] [Incident id: WNEXFKQ7-000049d4-00001228-00000000-1d4ed58b5502502-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507] [Threat score: 10] [Group: sm-detection] [Email: smultani@carbonblack.com] [Name: win-559j1nqvfgj] [Type and OS: WINDOWS pscr-sensor] [Severity: 10]\n", "eventTime": 1554651837865, "deviceInfo": { "deviceId": 18900, "targetPriorityCode": 0, "groupName": "sm-detection", "deviceName": "win-559j1nqvfgj", "deviceType": "WINDOWS", "email": "smultani@carbonblack.com", "deviceHostName": null, "deviceVersion": "pscr-sensor", "targetPriorityType": "MEDIUM", "uemId": null, "internalIpAddress": "192.168.81.148", "externalIpAddress": "73.69.152.214" }, "url": "https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-00001228-00000000-1d4ed58b5502502-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507", "ruleName": "sm-sentinel-notification", "type": "THREAT_HUNTER" }, { "threatHunterInfo": { "incidentId": "WNEXFKQ7-000049d4-00001228-00000000-1d4ed58b5502502-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507", "score": 10, "summary": "T1003 - Credential Dumping #2", "time": 1554652418330, "indicators": [ { "applicationName": "mimikatz.exe", "sha256Hash": "6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be", "indicatorName": "b7e9fd8e-febe-478c-8f44-2e90e0d10507-0" } ], "watchLists": [ { "id": "3ExgIixySwmbRuaXoxxKeA", "name": "Carbon Black Advanced Threats", "alert": true } ], "iocId": "b7e9fd8e-febe-478c-8f44-2e90e0d10507-0", "count": 0, "dismissed": false, "documentGuid": "FtA0ybjVRJuJ2VohA5E-Lw", "firstActivityTime": 1554651837865, "md5": "9e9ea5e8a16995124ba6e75bad4c6abe", "policyId": 9815, "processGuid": "WNEXFKQ7-000049d4-00001228-00000000-1d4ed58b5502502", "processPath": "c:\\users\\smultani\\music\\mimikatz_trunk (1)\\win32\\mimikatz.exe", "reportName": "T1003 - Credential Dumping #2", "reportId": "1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507", "reputation": "KNOWN_MALWARE", "responseAlarmId": "WNEXFKQ7-000049d4-00001228-00000000-1d4ed58b5502502-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507", "responseSeverity": 10, "runState": "RAN", "sha256": "6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be", "status": "UNRESOLVED", "tags": null, "targetPriority": "MEDIUM", "threatCause": { "reputation": "KNOWN_MALWARE", "actor": "6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be", "actorName": "mimikatz.exe", "reason": "Process mimikatz.exe was detected by the report \"T1003 - Credential Dumping #2\" in watchlist \"Carbon Black Advanced Threats\"", "actorType": null, "threatCategory": "RESPONSE_WATCHLIST", "actorProcessPPid": null, "causeEventId": null, "originSourceType": "UNKNOWN" }, "threatId": "5f1763e2ea26c424e8a84ec6b1090983", "lastUpdatedTime": 0, "orgId": 428 }, "eventDescription": "[sm-sentinel-watchlist] [Carbon Black has detected one or more threat indicator(s) on one of your devices.] [https://defense-eap01.conferdeploy.net/threat-hunter/analyze?processGUID=WNEXFKQ7-000049d4-00001228-00000000-1d4ed58b5502502&deviceId=18900] [T1003 - Credential Dumping #2] [Group: sm-detection] [Device Email: smultani@carbonblack.com] [Device Name: win-559j1nqvfgj] [Device Type: WINDOWS] [IOC: b7e9fd8e-febe-478c-8f44-2e90e0d10507-0] [Severity: 10]", "eventTime": 1554651837865, "deviceInfo": { "deviceId": 18900, "targetPriorityCode": 0, "groupName": "sm-detection", "deviceName": "win-559j1nqvfgj", "deviceType": "WINDOWS", "email": "smultani@carbonblack.com", "deviceHostName": null, "deviceVersion": "pscr-sensor", "targetPriorityType": "MEDIUM", "uemId": null, "internalIpAddress": "192.168.81.148", "externalIpAddress": "73.69.152.214" }, "url": "https://defense-eap01.conferdeploy.net", "ruleName": "sm-sentinel-watchlist", "type": "THREAT_HUNTER" } ], "success": true, "message": "Success" } cef_output_notification_th="""test CEF:0|CarbonBlack|CbDefense_Syslog_Connector|2.0|Threat_Hunter|PowerShell - File and Directory Discovery Enumeration|1|rt="Apr 07 2019 15:43:31" dvchost=win-559j1nqvfgj duser=smultani@carbonblack.com dvc=192.168.81.148 cs3Label="Link" cs3="https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-00001ef0-00000000-1d4ed58a5f07dbf-j0MkcneCQXy1fIbhber6rw-565660" cs4Label="Threat_ID" cs4="WNEXFKQ7-000049d4-00001ef0-00000000-1d4ed58a5f07dbf-j0MkcneCQXy1fIbhber6rw-565660" hash=ba4038fd20e474c047be8aad5bfacdb1bfc1ddbe12f803f473b7918d8d819436 test CEF:0|CarbonBlack|CbDefense_Syslog_Connector|2.0|Threat_Hunter|PowerShell - File and Directory Discovery Enumeration|1|rt="Apr 07 2019 15:43:31" dvchost=win-559j1nqvfgj duser=smultani@carbonblack.com dvc=192.168.81.148 cs3Label="Link" cs3="https://defense-eap01.conferdeploy.net" cs4Label="Threat_ID" cs4="WNEXFKQ7-000049d4-00001ef0-00000000-1d4ed58a5f07dbf-j0MkcneCQXy1fIbhber6rw-565660" hash=ba4038fd20e474c047be8aad5bfacdb1bfc1ddbe12f803f473b7918d8d819436 test CEF:0|CarbonBlack|CbDefense_Syslog_Connector|2.0|Threat_Hunter|T1003 - Credential Dumping #2|10|rt="Apr 07 2019 15:42:54" dvchost=win-559j1nqvfgj duser=smultani@carbonblack.com dvc=192.168.81.148 cs3Label="Link" cs3="https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-000013d8-00000000-1d4ed587c0142d0-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507" cs4Label="Threat_ID" cs4="WNEXFKQ7-000049d4-000013d8-00000000-1d4ed587c0142d0-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507" hash=6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be test CEF:0|CarbonBlack|CbDefense_Syslog_Connector|2.0|Threat_Hunter|T1003 - Credential Dumping #2|10|rt="Apr 07 2019 15:42:54" dvchost=win-559j1nqvfgj duser=smultani@carbonblack.com dvc=192.168.81.148 cs3Label="Link" cs3="https://defense-eap01.conferdeploy.net" cs4Label="Threat_ID" cs4="WNEXFKQ7-000049d4-000013d8-00000000-1d4ed587c0142d0-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507" hash=6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be test CEF:0|CarbonBlack|CbDefense_Syslog_Connector|2.0|Threat_Hunter|T1003 - Credential Dumping #2|10|rt="Apr 07 2019 15:39:10" dvchost=win-559j1nqvfgj duser=smultani@carbonblack.com dvc=192.168.81.148 cs3Label="Link" cs3="https://defense-eap01.conferdeploy.net" cs4Label="Threat_ID" cs4="WNEXFKQ7-000049d4-00000954-00000000-1d4ed5809bf5af8-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507" hash=6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be test CEF:0|CarbonBlack|CbDefense_Syslog_Connector|2.0|Threat_Hunter|T1003 - Credential Dumping #2|10|rt="Apr 07 2019 15:42:14" dvchost=win-559j1nqvfgj duser=smultani@carbonblack.com dvc=192.168.81.148 cs3Label="Link" cs3="https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-00001e18-00000000-1d4ed58784102f9-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507" cs4Label="Threat_ID" cs4="WNEXFKQ7-000049d4-00001e18-00000000-1d4ed58784102f9-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507" hash=38ff9593dcd07b0252ed3f1ad34ce7b538c522fd2a4d6ffef00f73767e75edac test CEF:0|CarbonBlack|CbDefense_Syslog_Connector|2.0|Threat_Hunter|T1003 - Credential Dumping #2|10|rt="Apr 07 2019 15:42:14" dvchost=win-559j1nqvfgj duser=smultani@carbonblack.com dvc=192.168.81.148 cs3Label="Link" cs3="https://defense-eap01.conferdeploy.net" cs4Label="Threat_ID" cs4="WNEXFKQ7-000049d4-00001e18-00000000-1d4ed58784102f9-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507" hash=38ff9593dcd07b0252ed3f1ad34ce7b538c522fd2a4d6ffef00f73767e75edac test CEF:0|CarbonBlack|CbDefense_Syslog_Connector|2.0|Threat_Hunter|T1003 - Credential Dumping #2|10|rt="Apr 07 2019 15:39:10" dvchost=win-559j1nqvfgj duser=smultani@carbonblack.com dvc=192.168.81.148 cs3Label="Link" cs3="https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-00000954-00000000-1d4ed5809bf5af8-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507" cs4Label="Threat_ID" cs4="WNEXFKQ7-000049d4-00000954-00000000-1d4ed5809bf5af8-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507" hash=6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be test CEF:0|CarbonBlack|CbDefense_Syslog_Connector|2.0|Threat_Hunter|Memory Grab using ProcDump|9|rt="Apr 07 2019 15:46:16" dvchost=win-559j1nqvfgj duser=smultani@carbonblack.com dvc=192.168.81.148 cs3Label="Link" cs3="https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-00000ac8-00000000-1d4ed590863aac9-n8JQkq8TuqkYoTiT5wObg-47a50561-e6ff-4106-8df1-5777f70a98d5" cs4Label="Threat_ID" cs4="WNEXFKQ7-000049d4-00000ac8-00000000-1d4ed590863aac9-n8JQkq8TuqkYoTiT5wObg-47a50561-e6ff-4106-8df1-5777f70a98d5" hash=16f413862efda3aba631d8a7ae2bfff6d84acd9f454a7adaa518c7a8a6f375a5 test CEF:0|CarbonBlack|CbDefense_Syslog_Connector|2.0|Threat_Hunter|T1003 - Credential Dumping #3|9|rt="Apr 07 2019 15:43:48" dvchost=win-559j1nqvfgj duser=smultani@carbonblack.com dvc=192.168.81.148 cs3Label="Link" cs3="https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-000011c4-00000000-1d4ed58af5a4ce9-1X7Zx5ZRbGc24xRp7IaQ-7aa6e57a-6fa8-423d-b997-427565bf7a06" cs4Label="Threat_ID" cs4="WNEXFKQ7-000049d4-000011c4-00000000-1d4ed58af5a4ce9-1X7Zx5ZRbGc24xRp7IaQ-7aa6e57a-6fa8-423d-b997-427565bf7a06" hash=05732e84de58a3cc142535431b3aa04efbe034cc96e837f93c360a6387d8faad test CEF:0|CarbonBlack|CbDefense_Syslog_Connector|2.0|Threat_Hunter|T1003 - Credential Dumping #2|10|rt="Apr 07 2019 15:43:57" dvchost=win-559j1nqvfgj duser=smultani@carbonblack.com dvc=192.168.81.148 cs3Label="Link" cs3="https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-00001228-00000000-1d4ed58b5502502-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507" cs4Label="Threat_ID" cs4="WNEXFKQ7-000049d4-00001228-00000000-1d4ed58b5502502-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507" hash=6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be test CEF:0|CarbonBlack|CbDefense_Syslog_Connector|2.0|Threat_Hunter|T1003 - Credential Dumping #2|10|rt="Apr 07 2019 15:43:57" dvchost=win-559j1nqvfgj duser=smultani@carbonblack.com dvc=192.168.81.148 cs3Label="Link" cs3="https://defense-eap01.conferdeploy.net" cs4Label="Threat_ID" cs4="WNEXFKQ7-000049d4-00001228-00000000-1d4ed58b5502502-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507" hash=6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be""" leef_output_notification_th="""LEEF:2.0|CarbonBlack|CbDefense|0.1|THREAT|x09|identHostName=win-559j1nqvfgj deviceName=win-559j1nqvfgj sev=1 deviceHostName= cat=THREAT_HUNTER externalIpAddress=73.69.152.214 deviceId=18900 sha256Hash=ba4038fd20e474c047be8aad5bfacdb1bfc1ddbe12f803f473b7918d8d819436 ruleName=sm-sentinel-notification identSrc=192.168.81.148 src=192.168.81.148 eventId=None uemId= resource=win-559j1nqvfgj targetPriorityCode=0 url=https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-00001ef0-00000000-1d4ed58a5f07dbf-j0MkcneCQXy1fIbhber6rw-565660 internalIpAddress=192.168.81.148 dst=192.168.81.148 summary=PowerShell - File and Directory Discovery Enumeration groupName=sm-detection reputation=TRUSTED_WHITE_LIST deviceType=WINDOWS devTime=Apr-07-2019 15:43:31 GMT targetPriorityType=MEDIUM signature=Threat_Hunter devTimeFormat=MMM dd yyyy HH:mm:ss z incidentId=WNEXFKQ7-000049d4-00001ef0-00000000-1d4ed58a5f07dbf-j0MkcneCQXy1fIbhber6rw-565660 type=THREAT email=smultani@carbonblack.com deviceVersion=pscr-sensor LEEF:2.0|CarbonBlack|CbDefense|0.1|565660-0|x09|identHostName=win-559j1nqvfgj deviceName=win-559j1nqvfgj sev=1 deviceHostName= cat=THREAT_HUNTER externalIpAddress=73.69.152.214 deviceId=18900 sha256Hash=ba4038fd20e474c047be8aad5bfacdb1bfc1ddbe12f803f473b7918d8d819436 ruleName=sm-sentinel-notification identSrc=192.168.81.148 src=192.168.81.148 eventId=None uemId= resource=win-559j1nqvfgj targetPriorityCode=0 url=https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-00001ef0-00000000-1d4ed58a5f07dbf-j0MkcneCQXy1fIbhber6rw-565660 internalIpAddress=192.168.81.148 dst=192.168.81.148 summary=PowerShell - File and Directory Discovery Enumeration groupName=sm-detection reputation=TRUSTED_WHITE_LIST deviceType=WINDOWS devTime=Apr-07-2019 15:43:31 GMT targetPriorityType=MEDIUM signature=Threat_Hunter devTimeFormat=MMM dd yyyy HH:mm:ss z incidentId=WNEXFKQ7-000049d4-00001ef0-00000000-1d4ed58a5f07dbf-j0MkcneCQXy1fIbhber6rw-565660 type=THREAT email=smultani@carbonblack.com deviceVersion=pscr-sensor applicationName=powershell.exe indicatorName=565660-0 sha256Hash=ba4038fd20e474c047be8aad5bfacdb1bfc1ddbe12f803f473b7918d8d819436 LEEF:2.0|CarbonBlack|CbDefense|0.1|THREAT|x09|identHostName=win-559j1nqvfgj deviceName=win-559j1nqvfgj sev=1 deviceHostName= cat=THREAT_HUNTER externalIpAddress=73.69.152.214 deviceId=18900 sha256Hash=ba4038fd20e474c047be8aad5bfacdb1bfc1ddbe12f803f473b7918d8d819436 ruleName=sm-sentinel-watchlist identSrc=192.168.81.148 src=192.168.81.148 eventId=None uemId= resource=win-559j1nqvfgj targetPriorityCode=0 url=https://defense-eap01.conferdeploy.net internalIpAddress=192.168.81.148 dst=192.168.81.148 summary=PowerShell - File and Directory Discovery Enumeration groupName=sm-detection reputation=TRUSTED_WHITE_LIST deviceType=WINDOWS devTime=Apr-07-2019 15:43:31 GMT targetPriorityType=MEDIUM signature=Threat_Hunter devTimeFormat=MMM dd yyyy HH:mm:ss z incidentId=WNEXFKQ7-000049d4-00001ef0-00000000-1d4ed58a5f07dbf-j0MkcneCQXy1fIbhber6rw-565660 type=THREAT email=smultani@carbonblack.com deviceVersion=pscr-sensor LEEF:2.0|CarbonBlack|CbDefense|0.1|565660-0|x09|identHostName=win-559j1nqvfgj deviceName=win-559j1nqvfgj sev=1 deviceHostName= cat=THREAT_HUNTER externalIpAddress=73.69.152.214 deviceId=18900 sha256Hash=ba4038fd20e474c047be8aad5bfacdb1bfc1ddbe12f803f473b7918d8d819436 ruleName=sm-sentinel-watchlist identSrc=192.168.81.148 src=192.168.81.148 eventId=None uemId= resource=win-559j1nqvfgj targetPriorityCode=0 url=https://defense-eap01.conferdeploy.net internalIpAddress=192.168.81.148 dst=192.168.81.148 summary=PowerShell - File and Directory Discovery Enumeration groupName=sm-detection reputation=TRUSTED_WHITE_LIST deviceType=WINDOWS devTime=Apr-07-2019 15:43:31 GMT targetPriorityType=MEDIUM signature=Threat_Hunter devTimeFormat=MMM dd yyyy HH:mm:ss z incidentId=WNEXFKQ7-000049d4-00001ef0-00000000-1d4ed58a5f07dbf-j0MkcneCQXy1fIbhber6rw-565660 type=THREAT email=smultani@carbonblack.com deviceVersion=pscr-sensor applicationName=powershell.exe indicatorName=565660-0 sha256Hash=ba4038fd20e474c047be8aad5bfacdb1bfc1ddbe12f803f473b7918d8d819436 LEEF:2.0|CarbonBlack|CbDefense|0.1|THREAT|x09|identHostName=win-559j1nqvfgj deviceName=win-559j1nqvfgj sev=10 deviceHostName= cat=THREAT_HUNTER externalIpAddress=73.69.152.214 deviceId=18900 sha256Hash=6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be ruleName=sm-sentinel-notification identSrc=192.168.81.148 src=192.168.81.148 eventId=None uemId= resource=win-559j1nqvfgj targetPriorityCode=0 url=https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-000013d8-00000000-1d4ed587c0142d0-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507 internalIpAddress=192.168.81.148 dst=192.168.81.148 summary=T1003 - Credential Dumping #2 groupName=sm-detection reputation=KNOWN_MALWARE deviceType=WINDOWS devTime=Apr-07-2019 15:42:54 GMT targetPriorityType=MEDIUM signature=Threat_Hunter devTimeFormat=MMM dd yyyy HH:mm:ss z incidentId=WNEXFKQ7-000049d4-000013d8-00000000-1d4ed587c0142d0-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507 type=THREAT email=smultani@carbonblack.com deviceVersion=pscr-sensor LEEF:2.0|CarbonBlack|CbDefense|0.1|b7e9fd8e-febe-478c-8f44-2e90e0d10507-0|x09|identHostName=win-559j1nqvfgj deviceName=win-559j1nqvfgj sev=10 deviceHostName= cat=THREAT_HUNTER externalIpAddress=73.69.152.214 deviceId=18900 sha256Hash=6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be ruleName=sm-sentinel-notification identSrc=192.168.81.148 src=192.168.81.148 eventId=None uemId= resource=win-559j1nqvfgj targetPriorityCode=0 url=https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-000013d8-00000000-1d4ed587c0142d0-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507 internalIpAddress=192.168.81.148 dst=192.168.81.148 summary=T1003 - Credential Dumping #2 groupName=sm-detection reputation=KNOWN_MALWARE deviceType=WINDOWS devTime=Apr-07-2019 15:42:54 GMT targetPriorityType=MEDIUM signature=Threat_Hunter devTimeFormat=MMM dd yyyy HH:mm:ss z incidentId=WNEXFKQ7-000049d4-000013d8-00000000-1d4ed587c0142d0-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507 type=THREAT email=smultani@carbonblack.com deviceVersion=pscr-sensor applicationName=mimikatz.exe indicatorName=b7e9fd8e-febe-478c-8f44-2e90e0d10507-0 sha256Hash=6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be LEEF:2.0|CarbonBlack|CbDefense|0.1|THREAT|x09|identHostName=win-559j1nqvfgj deviceName=win-559j1nqvfgj sev=10 deviceHostName= cat=THREAT_HUNTER externalIpAddress=73.69.152.214 deviceId=18900 sha256Hash=6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be ruleName=sm-sentinel-watchlist identSrc=192.168.81.148 src=192.168.81.148 eventId=None uemId= resource=win-559j1nqvfgj targetPriorityCode=0 url=https://defense-eap01.conferdeploy.net internalIpAddress=192.168.81.148 dst=192.168.81.148 summary=T1003 - Credential Dumping #2 groupName=sm-detection reputation=KNOWN_MALWARE deviceType=WINDOWS devTime=Apr-07-2019 15:42:54 GMT targetPriorityType=MEDIUM signature=Threat_Hunter devTimeFormat=MMM dd yyyy HH:mm:ss z incidentId=WNEXFKQ7-000049d4-000013d8-00000000-1d4ed587c0142d0-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507 type=THREAT email=smultani@carbonblack.com deviceVersion=pscr-sensor LEEF:2.0|CarbonBlack|CbDefense|0.1|b7e9fd8e-febe-478c-8f44-2e90e0d10507-0|x09|identHostName=win-559j1nqvfgj deviceName=win-559j1nqvfgj sev=10 deviceHostName= cat=THREAT_HUNTER externalIpAddress=73.69.152.214 deviceId=18900 sha256Hash=6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be ruleName=sm-sentinel-watchlist identSrc=192.168.81.148 src=192.168.81.148 eventId=None uemId= resource=win-559j1nqvfgj targetPriorityCode=0 url=https://defense-eap01.conferdeploy.net internalIpAddress=192.168.81.148 dst=192.168.81.148 summary=T1003 - Credential Dumping #2 groupName=sm-detection reputation=KNOWN_MALWARE deviceType=WINDOWS devTime=Apr-07-2019 15:42:54 GMT targetPriorityType=MEDIUM signature=Threat_Hunter devTimeFormat=MMM dd yyyy HH:mm:ss z incidentId=WNEXFKQ7-000049d4-000013d8-00000000-1d4ed587c0142d0-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507 type=THREAT email=smultani@carbonblack.com deviceVersion=pscr-sensor applicationName=mimikatz.exe indicatorName=b7e9fd8e-febe-478c-8f44-2e90e0d10507-0 sha256Hash=6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be LEEF:2.0|CarbonBlack|CbDefense|0.1|THREAT|x09|identHostName=win-559j1nqvfgj deviceName=win-559j1nqvfgj sev=10 deviceHostName= cat=THREAT_HUNTER externalIpAddress=73.69.152.214 deviceId=18900 sha256Hash=6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be ruleName=sm-sentinel-watchlist identSrc=192.168.81.148 src=192.168.81.148 eventId=None uemId= resource=win-559j1nqvfgj targetPriorityCode=0 url=https://defense-eap01.conferdeploy.net internalIpAddress=192.168.81.148 dst=192.168.81.148 summary=T1003 - Credential Dumping #2 groupName=sm-detection reputation=KNOWN_MALWARE deviceType=WINDOWS devTime=Apr-07-2019 15:39:10 GMT targetPriorityType=MEDIUM signature=Threat_Hunter devTimeFormat=MMM dd yyyy HH:mm:ss z incidentId=WNEXFKQ7-000049d4-00000954-00000000-1d4ed5809bf5af8-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507 type=THREAT email=smultani@carbonblack.com deviceVersion=pscr-sensor LEEF:2.0|CarbonBlack|CbDefense|0.1|b7e9fd8e-febe-478c-8f44-2e90e0d10507-0|x09|identHostName=win-559j1nqvfgj deviceName=win-559j1nqvfgj sev=10 deviceHostName= cat=THREAT_HUNTER externalIpAddress=73.69.152.214 deviceId=18900 sha256Hash=6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be ruleName=sm-sentinel-watchlist identSrc=192.168.81.148 src=192.168.81.148 eventId=None uemId= resource=win-559j1nqvfgj targetPriorityCode=0 url=https://defense-eap01.conferdeploy.net internalIpAddress=192.168.81.148 dst=192.168.81.148 summary=T1003 - Credential Dumping #2 groupName=sm-detection reputation=KNOWN_MALWARE deviceType=WINDOWS devTime=Apr-07-2019 15:39:10 GMT targetPriorityType=MEDIUM signature=Threat_Hunter devTimeFormat=MMM dd yyyy HH:mm:ss z incidentId=WNEXFKQ7-000049d4-00000954-00000000-1d4ed5809bf5af8-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507 type=THREAT email=smultani@carbonblack.com deviceVersion=pscr-sensor applicationName=mimikatz.exe indicatorName=b7e9fd8e-febe-478c-8f44-2e90e0d10507-0 sha256Hash=6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be LEEF:2.0|CarbonBlack|CbDefense|0.1|THREAT|x09|identHostName=win-559j1nqvfgj deviceName=win-559j1nqvfgj sev=10 deviceHostName= cat=THREAT_HUNTER externalIpAddress=73.69.152.214 deviceId=18900 sha256Hash=38ff9593dcd07b0252ed3f1ad34ce7b538c522fd2a4d6ffef00f73767e75edac ruleName=sm-sentinel-notification identSrc=192.168.81.148 src=192.168.81.148 eventId=None uemId= resource=win-559j1nqvfgj targetPriorityCode=0 url=https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-00001e18-00000000-1d4ed58784102f9-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507 internalIpAddress=192.168.81.148 dst=192.168.81.148 summary=T1003 - Credential Dumping #2 groupName=sm-detection reputation=PUP deviceType=WINDOWS devTime=Apr-07-2019 15:42:14 GMT targetPriorityType=MEDIUM signature=Threat_Hunter devTimeFormat=MMM dd yyyy HH:mm:ss z incidentId=WNEXFKQ7-000049d4-00001e18-00000000-1d4ed58784102f9-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507 type=THREAT email=smultani@carbonblack.com deviceVersion=pscr-sensor LEEF:2.0|CarbonBlack|CbDefense|0.1|b7e9fd8e-febe-478c-8f44-2e90e0d10507-0|x09|identHostName=win-559j1nqvfgj deviceName=win-559j1nqvfgj sev=10 deviceHostName= cat=THREAT_HUNTER externalIpAddress=73.69.152.214 deviceId=18900 sha256Hash=38ff9593dcd07b0252ed3f1ad34ce7b538c522fd2a4d6ffef00f73767e75edac ruleName=sm-sentinel-notification identSrc=192.168.81.148 src=192.168.81.148 eventId=None uemId= resource=win-559j1nqvfgj targetPriorityCode=0 url=https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-00001e18-00000000-1d4ed58784102f9-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507 internalIpAddress=192.168.81.148 dst=192.168.81.148 summary=T1003 - Credential Dumping #2 groupName=sm-detection reputation=PUP deviceType=WINDOWS devTime=Apr-07-2019 15:42:14 GMT targetPriorityType=MEDIUM signature=Threat_Hunter devTimeFormat=MMM dd yyyy HH:mm:ss z incidentId=WNEXFKQ7-000049d4-00001e18-00000000-1d4ed58784102f9-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507 type=THREAT email=smultani@carbonblack.com deviceVersion=pscr-sensor applicationName=mimikatz.exe indicatorName=b7e9fd8e-febe-478c-8f44-2e90e0d10507-0 sha256Hash=38ff9593dcd07b0252ed3f1ad34ce7b538c522fd2a4d6ffef00f73767e75edac LEEF:2.0|CarbonBlack|CbDefense|0.1|THREAT|x09|identHostName=win-559j1nqvfgj deviceName=win-559j1nqvfgj sev=10 deviceHostName= cat=THREAT_HUNTER externalIpAddress=73.69.152.214 deviceId=18900 sha256Hash=38ff9593dcd07b0252ed3f1ad34ce7b538c522fd2a4d6ffef00f73767e75edac ruleName=sm-sentinel-watchlist identSrc=192.168.81.148 src=192.168.81.148 eventId=None uemId= resource=win-559j1nqvfgj targetPriorityCode=0 url=https://defense-eap01.conferdeploy.net internalIpAddress=192.168.81.148 dst=192.168.81.148 summary=T1003 - Credential Dumping #2 groupName=sm-detection reputation=PUP deviceType=WINDOWS devTime=Apr-07-2019 15:42:14 GMT targetPriorityType=MEDIUM signature=Threat_Hunter devTimeFormat=MMM dd yyyy HH:mm:ss z incidentId=WNEXFKQ7-000049d4-00001e18-00000000-1d4ed58784102f9-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507 type=THREAT email=smultani@carbonblack.com deviceVersion=pscr-sensor LEEF:2.0|CarbonBlack|CbDefense|0.1|b7e9fd8e-febe-478c-8f44-2e90e0d10507-0|x09|identHostName=win-559j1nqvfgj deviceName=win-559j1nqvfgj sev=10 deviceHostName= cat=THREAT_HUNTER externalIpAddress=73.69.152.214 deviceId=18900 sha256Hash=38ff9593dcd07b0252ed3f1ad34ce7b538c522fd2a4d6ffef00f73767e75edac ruleName=sm-sentinel-watchlist identSrc=192.168.81.148 src=192.168.81.148 eventId=None uemId= resource=win-559j1nqvfgj targetPriorityCode=0 url=https://defense-eap01.conferdeploy.net internalIpAddress=192.168.81.148 dst=192.168.81.148 summary=T1003 - Credential Dumping #2 groupName=sm-detection reputation=PUP deviceType=WINDOWS devTime=Apr-07-2019 15:42:14 GMT targetPriorityType=MEDIUM signature=Threat_Hunter devTimeFormat=MMM dd yyyy HH:mm:ss z incidentId=WNEXFKQ7-000049d4-00001e18-00000000-1d4ed58784102f9-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507 type=THREAT email=smultani@carbonblack.com deviceVersion=pscr-sensor applicationName=mimikatz.exe indicatorName=b7e9fd8e-febe-478c-8f44-2e90e0d10507-0 sha256Hash=38ff9593dcd07b0252ed3f1ad34ce7b538c522fd2a4d6ffef00f73767e75edac LEEF:2.0|CarbonBlack|CbDefense|0.1|THREAT|x09|identHostName=win-559j1nqvfgj deviceName=win-559j1nqvfgj sev=10 deviceHostName= cat=THREAT_HUNTER externalIpAddress=73.69.152.214 deviceId=18900 sha256Hash=6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be ruleName=sm-sentinel-notification identSrc=192.168.81.148 src=192.168.81.148 eventId=None uemId= resource=win-559j1nqvfgj targetPriorityCode=0 url=https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-00000954-00000000-1d4ed5809bf5af8-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507 internalIpAddress=192.168.81.148 dst=192.168.81.148 summary=T1003 - Credential Dumping #2 groupName=sm-detection reputation=KNOWN_MALWARE deviceType=WINDOWS devTime=Apr-07-2019 15:39:10 GMT targetPriorityType=MEDIUM signature=Threat_Hunter devTimeFormat=MMM dd yyyy HH:mm:ss z incidentId=WNEXFKQ7-000049d4-00000954-00000000-1d4ed5809bf5af8-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507 type=THREAT email=smultani@carbonblack.com deviceVersion=pscr-sensor LEEF:2.0|CarbonBlack|CbDefense|0.1|b7e9fd8e-febe-478c-8f44-2e90e0d10507-0|x09|identHostName=win-559j1nqvfgj deviceName=win-559j1nqvfgj sev=10 deviceHostName= cat=THREAT_HUNTER externalIpAddress=73.69.152.214 deviceId=18900 sha256Hash=6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be ruleName=sm-sentinel-notification identSrc=192.168.81.148 src=192.168.81.148 eventId=None uemId= resource=win-559j1nqvfgj targetPriorityCode=0 url=https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-00000954-00000000-1d4ed5809bf5af8-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507 internalIpAddress=192.168.81.148 dst=192.168.81.148 summary=T1003 - Credential Dumping #2 groupName=sm-detection reputation=KNOWN_MALWARE deviceType=WINDOWS devTime=Apr-07-2019 15:39:10 GMT targetPriorityType=MEDIUM signature=Threat_Hunter devTimeFormat=MMM dd yyyy HH:mm:ss z incidentId=WNEXFKQ7-000049d4-00000954-00000000-1d4ed5809bf5af8-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507 type=THREAT email=smultani@carbonblack.com deviceVersion=pscr-sensor applicationName=mimikatz.exe indicatorName=b7e9fd8e-febe-478c-8f44-2e90e0d10507-0 sha256Hash=6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be LEEF:2.0|CarbonBlack|CbDefense|0.1|THREAT|x09|identHostName=win-559j1nqvfgj deviceName=win-559j1nqvfgj sev=9 deviceHostName= cat=THREAT_HUNTER externalIpAddress=73.69.152.214 deviceId=18900 sha256Hash=16f413862efda3aba631d8a7ae2bfff6d84acd9f454a7adaa518c7a8a6f375a5 ruleName=sm-sentinel-notification identSrc=192.168.81.148 src=192.168.81.148 eventId=None uemId= resource=win-559j1nqvfgj targetPriorityCode=0 url=https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-00000ac8-00000000-1d4ed590863aac9-n8JQkq8TuqkYoTiT5wObg-47a50561-e6ff-4106-8df1-5777f70a98d5 internalIpAddress=192.168.81.148 dst=192.168.81.148 summary=Memory Grab using ProcDump groupName=sm-detection reputation=TRUSTED_WHITE_LIST deviceType=WINDOWS devTime=Apr-07-2019 15:46:16 GMT targetPriorityType=MEDIUM signature=Threat_Hunter devTimeFormat=MMM dd yyyy HH:mm:ss z incidentId=WNEXFKQ7-000049d4-00000ac8-00000000-1d4ed590863aac9-n8JQkq8TuqkYoTiT5wObg-47a50561-e6ff-4106-8df1-5777f70a98d5 type=THREAT email=smultani@carbonblack.com deviceVersion=pscr-sensor LEEF:2.0|CarbonBlack|CbDefense|0.1|47a50561-e6ff-4106-8df1-5777f70a98d5-0|x09|identHostName=win-559j1nqvfgj deviceName=win-559j1nqvfgj sev=9 deviceHostName= cat=THREAT_HUNTER externalIpAddress=73.69.152.214 deviceId=18900 sha256Hash=16f413862efda3aba631d8a7ae2bfff6d84acd9f454a7adaa518c7a8a6f375a5 ruleName=sm-sentinel-notification identSrc=192.168.81.148 src=192.168.81.148 eventId=None uemId= resource=win-559j1nqvfgj targetPriorityCode=0 url=https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-00000ac8-00000000-1d4ed590863aac9-n8JQkq8TuqkYoTiT5wObg-47a50561-e6ff-4106-8df1-5777f70a98d5 internalIpAddress=192.168.81.148 dst=192.168.81.148 summary=Memory Grab using ProcDump groupName=sm-detection reputation=TRUSTED_WHITE_LIST deviceType=WINDOWS devTime=Apr-07-2019 15:46:16 GMT targetPriorityType=MEDIUM signature=Threat_Hunter devTimeFormat=MMM dd yyyy HH:mm:ss z incidentId=WNEXFKQ7-000049d4-00000ac8-00000000-1d4ed590863aac9-n8JQkq8TuqkYoTiT5wObg-47a50561-e6ff-4106-8df1-5777f70a98d5 type=THREAT email=smultani@carbonblack.com deviceVersion=pscr-sensor applicationName=procdump64.exe indicatorName=47a50561-e6ff-4106-8df1-5777f70a98d5-0 sha256Hash=16f413862efda3aba631d8a7ae2bfff6d84acd9f454a7adaa518c7a8a6f375a5 LEEF:2.0|CarbonBlack|CbDefense|0.1|THREAT|x09|identHostName=win-559j1nqvfgj deviceName=win-559j1nqvfgj sev=9 deviceHostName= cat=THREAT_HUNTER externalIpAddress=73.69.152.214 deviceId=18900 sha256Hash=05732e84de58a3cc142535431b3aa04efbe034cc96e837f93c360a6387d8faad ruleName=sm-sentinel-notification identSrc=192.168.81.148 src=192.168.81.148 eventId=None uemId= resource=win-559j1nqvfgj targetPriorityCode=0 url=https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-000011c4-00000000-1d4ed58af5a4ce9-1X7Zx5ZRbGc24xRp7IaQ-7aa6e57a-6fa8-423d-b997-427565bf7a06 internalIpAddress=192.168.81.148 dst=192.168.81.148 summary=T1003 - Credential Dumping #3 groupName=sm-detection reputation=TRUSTED_WHITE_LIST deviceType=WINDOWS devTime=Apr-07-2019 15:43:48 GMT targetPriorityType=MEDIUM signature=Threat_Hunter devTimeFormat=MMM dd yyyy HH:mm:ss z incidentId=WNEXFKQ7-000049d4-000011c4-00000000-1d4ed58af5a4ce9-1X7Zx5ZRbGc24xRp7IaQ-7aa6e57a-6fa8-423d-b997-427565bf7a06 type=THREAT email=smultani@carbonblack.com deviceVersion=pscr-sensor LEEF:2.0|CarbonBlack|CbDefense|0.1|7aa6e57a-6fa8-423d-b997-427565bf7a06-0|x09|identHostName=win-559j1nqvfgj deviceName=win-559j1nqvfgj sev=9 deviceHostName= cat=THREAT_HUNTER externalIpAddress=73.69.152.214 deviceId=18900 sha256Hash=05732e84de58a3cc142535431b3aa04efbe034cc96e837f93c360a6387d8faad ruleName=sm-sentinel-notification identSrc=192.168.81.148 src=192.168.81.148 eventId=None uemId= resource=win-559j1nqvfgj targetPriorityCode=0 url=https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-000011c4-00000000-1d4ed58af5a4ce9-1X7Zx5ZRbGc24xRp7IaQ-7aa6e57a-6fa8-423d-b997-427565bf7a06 internalIpAddress=192.168.81.148 dst=192.168.81.148 summary=T1003 - Credential Dumping #3 groupName=sm-detection reputation=TRUSTED_WHITE_LIST deviceType=WINDOWS devTime=Apr-07-2019 15:43:48 GMT targetPriorityType=MEDIUM signature=Threat_Hunter devTimeFormat=MMM dd yyyy HH:mm:ss z incidentId=WNEXFKQ7-000049d4-000011c4-00000000-1d4ed58af5a4ce9-1X7Zx5ZRbGc24xRp7IaQ-7aa6e57a-6fa8-423d-b997-427565bf7a06 type=THREAT email=smultani@carbonblack.com deviceVersion=pscr-sensor applicationName=procdump.exe indicatorName=7aa6e57a-6fa8-423d-b997-427565bf7a06-0 sha256Hash=05732e84de58a3cc142535431b3aa04efbe034cc96e837f93c360a6387d8faad LEEF:2.0|CarbonBlack|CbDefense|0.1|THREAT|x09|identHostName=win-559j1nqvfgj deviceName=win-559j1nqvfgj sev=10 deviceHostName= cat=THREAT_HUNTER externalIpAddress=73.69.152.214 deviceId=18900 sha256Hash=6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be ruleName=sm-sentinel-notification identSrc=192.168.81.148 src=192.168.81.148 eventId=None uemId= resource=win-559j1nqvfgj targetPriorityCode=0 url=https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-00001228-00000000-1d4ed58b5502502-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507 internalIpAddress=192.168.81.148 dst=192.168.81.148 summary=T1003 - Credential Dumping #2 groupName=sm-detection reputation=KNOWN_MALWARE deviceType=WINDOWS devTime=Apr-07-2019 15:43:57 GMT targetPriorityType=MEDIUM signature=Threat_Hunter devTimeFormat=MMM dd yyyy HH:mm:ss z incidentId=WNEXFKQ7-000049d4-00001228-00000000-1d4ed58b5502502-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507 type=THREAT email=smultani@carbonblack.com deviceVersion=pscr-sensor LEEF:2.0|CarbonBlack|CbDefense|0.1|b7e9fd8e-febe-478c-8f44-2e90e0d10507-0|x09|identHostName=win-559j1nqvfgj deviceName=win-559j1nqvfgj sev=10 deviceHostName= cat=THREAT_HUNTER externalIpAddress=73.69.152.214 deviceId=18900 sha256Hash=6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be ruleName=sm-sentinel-notification identSrc=192.168.81.148 src=192.168.81.148 eventId=None uemId= resource=win-559j1nqvfgj targetPriorityCode=0 url=https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-00001228-00000000-1d4ed58b5502502-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507 internalIpAddress=192.168.81.148 dst=192.168.81.148 summary=T1003 - Credential Dumping #2 groupName=sm-detection reputation=KNOWN_MALWARE deviceType=WINDOWS devTime=Apr-07-2019 15:43:57 GMT targetPriorityType=MEDIUM signature=Threat_Hunter devTimeFormat=MMM dd yyyy HH:mm:ss z incidentId=WNEXFKQ7-000049d4-00001228-00000000-1d4ed58b5502502-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507 type=THREAT email=smultani@carbonblack.com deviceVersion=pscr-sensor applicationName=mimikatz.exe indicatorName=b7e9fd8e-febe-478c-8f44-2e90e0d10507-0 sha256Hash=6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be LEEF:2.0|CarbonBlack|CbDefense|0.1|THREAT|x09|identHostName=win-559j1nqvfgj deviceName=win-559j1nqvfgj sev=10 deviceHostName= cat=THREAT_HUNTER externalIpAddress=73.69.152.214 deviceId=18900 sha256Hash=6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be ruleName=sm-sentinel-watchlist identSrc=192.168.81.148 src=192.168.81.148 eventId=None uemId= resource=win-559j1nqvfgj targetPriorityCode=0 url=https://defense-eap01.conferdeploy.net internalIpAddress=192.168.81.148 dst=192.168.81.148 summary=T1003 - Credential Dumping #2 groupName=sm-detection reputation=KNOWN_MALWARE deviceType=WINDOWS devTime=Apr-07-2019 15:43:57 GMT targetPriorityType=MEDIUM signature=Threat_Hunter devTimeFormat=MMM dd yyyy HH:mm:ss z incidentId=WNEXFKQ7-000049d4-00001228-00000000-1d4ed58b5502502-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507 type=THREAT email=smultani@carbonblack.com deviceVersion=pscr-sensor LEEF:2.0|CarbonBlack|CbDefense|0.1|b7e9fd8e-febe-478c-8f44-2e90e0d10507-0|x09|identHostName=win-559j1nqvfgj deviceName=win-559j1nqvfgj sev=10 deviceHostName= cat=THREAT_HUNTER externalIpAddress=73.69.152.214 deviceId=18900 sha256Hash=6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be ruleName=sm-sentinel-watchlist identSrc=192.168.81.148 src=192.168.81.148 eventId=None uemId= resource=win-559j1nqvfgj targetPriorityCode=0 url=https://defense-eap01.conferdeploy.net internalIpAddress=192.168.81.148 dst=192.168.81.148 summary=T1003 - Credential Dumping #2 groupName=sm-detection reputation=KNOWN_MALWARE deviceType=WINDOWS devTime=Apr-07-2019 15:43:57 GMT targetPriorityType=MEDIUM signature=Threat_Hunter devTimeFormat=MMM dd yyyy HH:mm:ss z incidentId=WNEXFKQ7-000049d4-00001228-00000000-1d4ed58b5502502-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507 type=THREAT email=smultani@carbonblack.com deviceVersion=pscr-sensor applicationName=mimikatz.exe indicatorName=b7e9fd8e-febe-478c-8f44-2e90e0d10507-0 sha256Hash=6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be """ json_output_notification_th=[{'eventTime': 1554651811577, 'eventDescription': '[sm-sentinel-notification] [Carbon Black has detected a threat against your company.] [https://defense-eap01.conferdeploy.net#device/18900/incident/WNEXFKQ7-000049d4-00001ef0-00000000-1d4ed58a5f07dbf-j0MkcneCQXy1fIbhber6rw-565660] [PowerShell - File and Directory Discovery Enumeration] [Incident id: WNEXFKQ7-000049d4-00001ef0-00000000-1d4ed58a5f07dbf-j0MkcneCQXy1fIbhber6rw-565660] [Threat score: 1] [Group: sm-detection] [Email: smultani@carbonblack.com] [Name: win-559j1nqvfgj] [Type and OS: WINDOWS pscr-sensor] [Severity: 1]\n', 'url': 'https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-00001ef0-00000000-1d4ed58a5f07dbf-j0MkcneCQXy1fIbhber6rw-565660', 'deviceInfo': {'deviceName': 'win-559j1nqvfgj', 'deviceHostName': '', 'externalIpAddress': '73.69.152.214', 'deviceId': 18900, 'uemId': '', 'targetPriorityCode': 0, 'internalIpAddress': '192.168.81.148', 'groupName': 'sm-detection', 'deviceType': 'WINDOWS', 'deviceVersion': 'pscr-sensor', 'email': 'smultani@carbonblack.com', 'targetPriorityType': 'MEDIUM'}, 'source': 'test', 'ruleName': 'sm-sentinel-notification', 'threatHunterInfo': {'responseSeverity': 1, 'reportName': 'PowerShell - File and Directory Discovery Enumeration', 'documentGuid': '7a9fQEsTRfuFmXcogI8CMQ', 'runState': 'RAN', 'firstActivityTime': 1554651811577, 'dismissed': 'false', 'targetPriority': 'MEDIUM', 'score': 1, 'indicators': [{'applicationName': 'powershell.exe', 'indicatorName': '565660-0', 'sha256Hash': 'ba4038fd20e474c047be8aad5bfacdb1bfc1ddbe12f803f473b7918d8d819436'}], 'sha256': 'ba4038fd20e474c047be8aad5bfacdb1bfc1ddbe12f803f473b7918d8d819436', 'status': 'UNRESOLVED', 'processPath': 'c:\\windows\\system32\\windowspowershell\\v1.0\\powershell.exe', 'tags': '', 'watchLists': [{'alert': 'true', 'id': 'a3xW2ZiaRyAqRtuVES8Q', 'name': 'ATT&CK Framework'}], 'time': 1554652050250, 'reportId': 'j0MkcneCQXy1fIbhber6rw-565660', 'responseAlarmId': 'WNEXFKQ7-000049d4-00001ef0-00000000-1d4ed58a5f07dbf-j0MkcneCQXy1fIbhber6rw-565660', 'iocId': '565660-0', 'md5': '097ce5761c89434367598b34fe32893b', 'count': 0, 'threatCause': {'actorProcessPPid': '', 'reason': 'Process powershell.exe was detected by the report "PowerShell - File and Directory Discovery Enumeration" in watchlist "ATT&CK Framework"', 'reputation': 'TRUSTED_WHITE_LIST', 'threatCategory': 'RESPONSE_WATCHLIST', 'actorName': 'powershell.exe', 'causeEventId': '', 'actorType': '', 'originSourceType': 'UNKNOWN', 'actor': 'ba4038fd20e474c047be8aad5bfacdb1bfc1ddbe12f803f473b7918d8d819436'}, 'lastUpdatedTime': 0, 'threatId': 'a2b724aa094af97c06c758d325240460', 'summary': 'PowerShell - File and Directory Discovery Enumeration', 'reputation': 'TRUSTED_WHITE_LIST', 'orgId': 428, 'policyId': 9815, 'processGuid': 'WNEXFKQ7-000049d4-00001ef0-00000000-1d4ed58a5f07dbf', 'incidentId': 'WNEXFKQ7-000049d4-00001ef0-00000000-1d4ed58a5f07dbf-j0MkcneCQXy1fIbhber6rw-565660'}, 'type': 'THREAT_HUNTER'}, {'eventTime': 1554651811577, 'eventDescription': '[sm-sentinel-watchlist] [Carbon Black has detected one or more threat indicator(s) on one of your devices.] [https://defense-eap01.conferdeploy.net/threat-hunter/analyze?processGUID=WNEXFKQ7-000049d4-00001ef0-00000000-1d4ed58a5f07dbf&deviceId=18900] [PowerShell - File and Directory Discovery Enumeration] [Group: sm-detection] [Device Email: smultani@carbonblack.com] [Device Name: win-559j1nqvfgj] [Device Type: WINDOWS] [IOC: 565660-0] [Severity: 1]', 'url': 'https://defense-eap01.conferdeploy.net', 'deviceInfo': {'deviceName': 'win-559j1nqvfgj', 'deviceHostName': '', 'externalIpAddress': '73.69.152.214', 'deviceId': 18900, 'uemId': '', 'targetPriorityCode': 0, 'internalIpAddress': '192.168.81.148', 'groupName': 'sm-detection', 'deviceType': 'WINDOWS', 'deviceVersion': 'pscr-sensor', 'email': 'smultani@carbonblack.com', 'targetPriorityType': 'MEDIUM'}, 'source': 'test', 'ruleName': 'sm-sentinel-watchlist', 'threatHunterInfo': {'responseSeverity': 1, 'reportName': 'PowerShell - File and Directory Discovery Enumeration', 'documentGuid': '7a9fQEsTRfuFmXcogI8CMQ', 'runState': 'RAN', 'firstActivityTime': 1554651811577, 'dismissed': 'false', 'targetPriority': 'MEDIUM', 'score': 1, 'indicators': [{'applicationName': 'powershell.exe', 'indicatorName': '565660-0', 'sha256Hash': 'ba4038fd20e474c047be8aad5bfacdb1bfc1ddbe12f803f473b7918d8d819436'}], 'sha256': 'ba4038fd20e474c047be8aad5bfacdb1bfc1ddbe12f803f473b7918d8d819436', 'status': 'UNRESOLVED', 'processPath': 'c:\\windows\\system32\\windowspowershell\\v1.0\\powershell.exe', 'tags': '', 'watchLists': [{'alert': 'true', 'id': 'a3xW2ZiaRyAqRtuVES8Q', 'name': 'ATT&CK Framework'}], 'time': 1554652050260, 'reportId': 'j0MkcneCQXy1fIbhber6rw-565660', 'responseAlarmId': 'WNEXFKQ7-000049d4-00001ef0-00000000-1d4ed58a5f07dbf-j0MkcneCQXy1fIbhber6rw-565660', 'iocId': '565660-0', 'md5': '097ce5761c89434367598b34fe32893b', 'count': 0, 'threatCause': {'actorProcessPPid': '', 'reason': 'Process powershell.exe was detected by the report "PowerShell - File and Directory Discovery Enumeration" in watchlist "ATT&CK Framework"', 'reputation': 'TRUSTED_WHITE_LIST', 'threatCategory': 'RESPONSE_WATCHLIST', 'actorName': 'powershell.exe', 'causeEventId': '', 'actorType': '', 'originSourceType': 'UNKNOWN', 'actor': 'ba4038fd20e474c047be8aad5bfacdb1bfc1ddbe12f803f473b7918d8d819436'}, 'lastUpdatedTime': 0, 'threatId': 'a2b724aa094af97c06c758d325240460', 'summary': 'PowerShell - File and Directory Discovery Enumeration', 'reputation': 'TRUSTED_WHITE_LIST', 'orgId': 428, 'policyId': 9815, 'processGuid': 'WNEXFKQ7-000049d4-00001ef0-00000000-1d4ed58a5f07dbf', 'incidentId': 'WNEXFKQ7-000049d4-00001ef0-00000000-1d4ed58a5f07dbf-j0MkcneCQXy1fIbhber6rw-565660'}, 'type': 'THREAT_HUNTER'}, {'eventTime': 1554651774855, 'eventDescription': '[sm-sentinel-notification] [Carbon Black has detected a threat against your company.] [https://defense-eap01.conferdeploy.net#device/18900/incident/WNEXFKQ7-000049d4-000013d8-00000000-1d4ed587c0142d0-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507] [T1003 - Credential Dumping #2] [Incident id: WNEXFKQ7-000049d4-000013d8-00000000-1d4ed587c0142d0-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507] [Threat score: 10] [Group: sm-detection] [Email: smultani@carbonblack.com] [Name: win-559j1nqvfgj] [Type and OS: WINDOWS pscr-sensor] [Severity: 10]\n', 'url': 'https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-000013d8-00000000-1d4ed587c0142d0-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507', 'deviceInfo': {'deviceName': 'win-559j1nqvfgj', 'deviceHostName': '', 'externalIpAddress': '73.69.152.214', 'deviceId': 18900, 'uemId': '', 'targetPriorityCode': 0, 'internalIpAddress': '192.168.81.148', 'groupName': 'sm-detection', 'deviceType': 'WINDOWS', 'deviceVersion': 'pscr-sensor', 'email': 'smultani@carbonblack.com', 'targetPriorityType': 'MEDIUM'}, 'source': 'test', 'ruleName': 'sm-sentinel-notification', 'threatHunterInfo': {'responseSeverity': 10, 'reportName': 'T1003 - Credential Dumping #2', 'documentGuid': 'NoKzSz7wTzSil0ur7wYG0Q', 'runState': 'RAN', 'firstActivityTime': 1554651774855, 'dismissed': 'false', 'targetPriority': 'MEDIUM', 'score': 10, 'indicators': [{'applicationName': 'mimikatz.exe', 'indicatorName': 'b7e9fd8e-febe-478c-8f44-2e90e0d10507-0', 'sha256Hash': '6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be'}], 'sha256': '6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be', 'status': 'UNRESOLVED', 'processPath': 'c:\\users\\smultani\\music\\mimikatz_trunk (1)\\win32\\mimikatz.exe', 'tags': '', 'watchLists': [{'alert': 'true', 'id': '3ExgIixySwmbRuaXoxxKeA', 'name': 'Carbon Black Advanced Threats'}], 'time': 1554652058988, 'reportId': '1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507', 'responseAlarmId': 'WNEXFKQ7-000049d4-000013d8-00000000-1d4ed587c0142d0-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507', 'iocId': 'b7e9fd8e-febe-478c-8f44-2e90e0d10507-0', 'md5': '9e9ea5e8a16995124ba6e75bad4c6abe', 'count': 0, 'threatCause': {'actorProcessPPid': '', 'reason': 'Process mimikatz.exe was detected by the report "T1003 - Credential Dumping #2" in watchlist "Carbon Black Advanced Threats"', 'reputation': 'KNOWN_MALWARE', 'threatCategory': 'RESPONSE_WATCHLIST', 'actorName': 'mimikatz.exe', 'causeEventId': '', 'actorType': '', 'originSourceType': 'UNKNOWN', 'actor': '6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be'}, 'lastUpdatedTime': 0, 'threatId': '5f1763e2ea26c424e8a84ec6b1090983', 'summary': 'T1003 - Credential Dumping #2', 'reputation': 'KNOWN_MALWARE', 'orgId': 428, 'policyId': 9815, 'processGuid': 'WNEXFKQ7-000049d4-000013d8-00000000-1d4ed587c0142d0', 'incidentId': 'WNEXFKQ7-000049d4-000013d8-00000000-1d4ed587c0142d0-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507'}, 'type': 'THREAT_HUNTER'}, {'eventTime': 1554651774855, 'eventDescription': '[sm-sentinel-watchlist] [Carbon Black has detected one or more threat indicator(s) on one of your devices.] [https://defense-eap01.conferdeploy.net/threat-hunter/analyze?processGUID=WNEXFKQ7-000049d4-000013d8-00000000-1d4ed587c0142d0&deviceId=18900] [T1003 - Credential Dumping #2] [Group: sm-detection] [Device Email: smultani@carbonblack.com] [Device Name: win-559j1nqvfgj] [Device Type: WINDOWS] [IOC: b7e9fd8e-febe-478c-8f44-2e90e0d10507-0] [Severity: 10]', 'url': 'https://defense-eap01.conferdeploy.net', 'deviceInfo': {'deviceName': 'win-559j1nqvfgj', 'deviceHostName': '', 'externalIpAddress': '73.69.152.214', 'deviceId': 18900, 'uemId': '', 'targetPriorityCode': 0, 'internalIpAddress': '192.168.81.148', 'groupName': 'sm-detection', 'deviceType': 'WINDOWS', 'deviceVersion': 'pscr-sensor', 'email': 'smultani@carbonblack.com', 'targetPriorityType': 'MEDIUM'}, 'source': 'test', 'ruleName': 'sm-sentinel-watchlist', 'threatHunterInfo': {'responseSeverity': 10, 'reportName': 'T1003 - Credential Dumping #2', 'documentGuid': 'NoKzSz7wTzSil0ur7wYG0Q', 'runState': 'RAN', 'firstActivityTime': 1554651774855, 'dismissed': 'false', 'targetPriority': 'MEDIUM', 'score': 10, 'indicators': [{'applicationName': 'mimikatz.exe', 'indicatorName': 'b7e9fd8e-febe-478c-8f44-2e90e0d10507-0', 'sha256Hash': '6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be'}], 'sha256': '6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be', 'status': 'UNRESOLVED', 'processPath': 'c:\\users\\smultani\\music\\mimikatz_trunk (1)\\win32\\mimikatz.exe', 'tags': '', 'watchLists': [{'alert': 'true', 'id': '3ExgIixySwmbRuaXoxxKeA', 'name': 'Carbon Black Advanced Threats'}], 'time': 1554652058999, 'reportId': '1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507', 'responseAlarmId': 'WNEXFKQ7-000049d4-000013d8-00000000-1d4ed587c0142d0-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507', 'iocId': 'b7e9fd8e-febe-478c-8f44-2e90e0d10507-0', 'md5': '9e9ea5e8a16995124ba6e75bad4c6abe', 'count': 0, 'threatCause': {'actorProcessPPid': '', 'reason': 'Process mimikatz.exe was detected by the report "T1003 - Credential Dumping #2" in watchlist "Carbon Black Advanced Threats"', 'reputation': 'KNOWN_MALWARE', 'threatCategory': 'RESPONSE_WATCHLIST', 'actorName': 'mimikatz.exe', 'causeEventId': '', 'actorType': '', 'originSourceType': 'UNKNOWN', 'actor': '6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be'}, 'lastUpdatedTime': 0, 'threatId': '5f1763e2ea26c424e8a84ec6b1090983', 'summary': 'T1003 - Credential Dumping #2', 'reputation': 'KNOWN_MALWARE', 'orgId': 428, 'policyId': 9815, 'processGuid': 'WNEXFKQ7-000049d4-000013d8-00000000-1d4ed587c0142d0', 'incidentId': 'WNEXFKQ7-000049d4-000013d8-00000000-1d4ed587c0142d0-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507'}, 'type': 'THREAT_HUNTER'}, {'eventTime': 1554651550298, 'eventDescription': '[sm-sentinel-watchlist] [Carbon Black has detected one or more threat indicator(s) on one of your devices.] [https://defense-eap01.conferdeploy.net/threat-hunter/analyze?processGUID=WNEXFKQ7-000049d4-00000954-00000000-1d4ed5809bf5af8&deviceId=18900] [T1003 - Credential Dumping #2] [Group: sm-detection] [Device Email: smultani@carbonblack.com] [Device Name: win-559j1nqvfgj] [Device Type: WINDOWS] [IOC: b7e9fd8e-febe-478c-8f44-2e90e0d10507-0] [Severity: 10]', 'url': 'https://defense-eap01.conferdeploy.net', 'deviceInfo': {'deviceName': 'win-559j1nqvfgj', 'deviceHostName': '', 'externalIpAddress': '73.69.152.214', 'deviceId': 18900, 'uemId': '', 'targetPriorityCode': 0, 'internalIpAddress': '192.168.81.148', 'groupName': 'sm-detection', 'deviceType': 'WINDOWS', 'deviceVersion': 'pscr-sensor', 'email': 'smultani@carbonblack.com', 'targetPriorityType': 'MEDIUM'}, 'source': 'test', 'ruleName': 'sm-sentinel-watchlist', 'threatHunterInfo': {'responseSeverity': 10, 'reportName': 'T1003 - Credential Dumping #2', 'documentGuid': 'F-OinTckReGkfHVvNZqe1w', 'runState': 'RAN', 'firstActivityTime': 1554651550298, 'dismissed': 'false', 'targetPriority': 'MEDIUM', 'score': 10, 'indicators': [{'applicationName': 'mimikatz.exe', 'indicatorName': 'b7e9fd8e-febe-478c-8f44-2e90e0d10507-0', 'sha256Hash': '6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be'}], 'sha256': '6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be', 'status': 'UNRESOLVED', 'processPath': 'c:\\users\\smultani\\desktop\\mimikatz_trunk (1)\\win32\\mimikatz.exe', 'tags': '', 'watchLists': [{'alert': 'true', 'id': '3ExgIixySwmbRuaXoxxKeA', 'name': 'Carbon Black Advanced Threats'}], 'time': 1554652062174, 'reportId': '1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507', 'responseAlarmId': 'WNEXFKQ7-000049d4-00000954-00000000-1d4ed5809bf5af8-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507', 'iocId': 'b7e9fd8e-febe-478c-8f44-2e90e0d10507-0', 'md5': '9e9ea5e8a16995124ba6e75bad4c6abe', 'count': 0, 'threatCause': {'actorProcessPPid': '', 'reason': 'Process mimikatz.exe was detected by the report "T1003 - Credential Dumping #2" in watchlist "Carbon Black Advanced Threats"', 'reputation': 'KNOWN_MALWARE', 'threatCategory': 'RESPONSE_WATCHLIST', 'actorName': 'mimikatz.exe', 'causeEventId': '', 'actorType': '', 'originSourceType': 'UNKNOWN', 'actor': '6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be'}, 'lastUpdatedTime': 0, 'threatId': '5f1763e2ea26c424e8a84ec6b1090983', 'summary': 'T1003 - Credential Dumping #2', 'reputation': 'KNOWN_MALWARE', 'orgId': 428, 'policyId': 9815, 'processGuid': 'WNEXFKQ7-000049d4-00000954-00000000-1d4ed5809bf5af8', 'incidentId': 'WNEXFKQ7-000049d4-00000954-00000000-1d4ed5809bf5af8-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507'}, 'type': 'THREAT_HUNTER'}, {'eventTime': 1554651734686, 'eventDescription': '[sm-sentinel-notification] [Carbon Black has detected a threat against your company.] [https://defense-eap01.conferdeploy.net#device/18900/incident/WNEXFKQ7-000049d4-00001e18-00000000-1d4ed58784102f9-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507] [T1003 - Credential Dumping #2] [Incident id: WNEXFKQ7-000049d4-00001e18-00000000-1d4ed58784102f9-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507] [Threat score: 10] [Group: sm-detection] [Email: smultani@carbonblack.com] [Name: win-559j1nqvfgj] [Type and OS: WINDOWS pscr-sensor] [Severity: 10]\n', 'url': 'https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-00001e18-00000000-1d4ed58784102f9-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507', 'deviceInfo': {'deviceName': 'win-559j1nqvfgj', 'deviceHostName': '', 'externalIpAddress': '73.69.152.214', 'deviceId': 18900, 'uemId': '', 'targetPriorityCode': 0, 'internalIpAddress': '192.168.81.148', 'groupName': 'sm-detection', 'deviceType': 'WINDOWS', 'deviceVersion': 'pscr-sensor', 'email': 'smultani@carbonblack.com', 'targetPriorityType': 'MEDIUM'}, 'source': 'test', 'ruleName': 'sm-sentinel-notification', 'threatHunterInfo': {'responseSeverity': 10, 'reportName': 'T1003 - Credential Dumping #2', 'documentGuid': 'qgp18td2TFK2Dw3YB2MuSA', 'runState': 'RAN', 'firstActivityTime': 1554651734686, 'dismissed': 'false', 'targetPriority': 'MEDIUM', 'score': 10, 'indicators': [{'applicationName': 'mimikatz.exe', 'indicatorName': 'b7e9fd8e-febe-478c-8f44-2e90e0d10507-0', 'sha256Hash': '38ff9593dcd07b0252ed3f1ad34ce7b538c522fd2a4d6ffef00f73767e75edac'}], 'sha256': '38ff9593dcd07b0252ed3f1ad34ce7b538c522fd2a4d6ffef00f73767e75edac', 'status': 'UNRESOLVED', 'processPath': 'c:\\users\\smultani\\music\\mimikatz_trunk (1)\\d\\mimikatz.exe', 'tags': '', 'watchLists': [{'alert': 'true', 'id': '3ExgIixySwmbRuaXoxxKeA', 'name': 'Carbon Black Advanced Threats'}], 'time': 1554652062191, 'reportId': '1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507', 'responseAlarmId': 'WNEXFKQ7-000049d4-00001e18-00000000-1d4ed58784102f9-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507', 'iocId': 'b7e9fd8e-febe-478c-8f44-2e90e0d10507-0', 'md5': 'a3298b7614ff07f91301655edd58e9d7', 'count': 0, 'threatCause': {'actorProcessPPid': '', 'reason': 'Process mimikatz.exe was detected by the report "T1003 - Credential Dumping #2" in watchlist "Carbon Black Advanced Threats"', 'reputation': 'PUP', 'threatCategory': 'RESPONSE_WATCHLIST', 'actorName': 'mimikatz.exe', 'causeEventId': '', 'actorType': '', 'originSourceType': 'UNKNOWN', 'actor': '38ff9593dcd07b0252ed3f1ad34ce7b538c522fd2a4d6ffef00f73767e75edac'}, 'lastUpdatedTime': 0, 'threatId': '5f1763e2ea26c424e8a84ec6b1090983', 'summary': 'T1003 - Credential Dumping #2', 'reputation': 'PUP', 'orgId': 428, 'policyId': 9815, 'processGuid': 'WNEXFKQ7-000049d4-00001e18-00000000-1d4ed58784102f9', 'incidentId': 'WNEXFKQ7-000049d4-00001e18-00000000-1d4ed58784102f9-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507'}, 'type': 'THREAT_HUNTER'}, {'eventTime': 1554651734686, 'eventDescription': '[sm-sentinel-watchlist] [Carbon Black has detected one or more threat indicator(s) on one of your devices.] [https://defense-eap01.conferdeploy.net/threat-hunter/analyze?processGUID=WNEXFKQ7-000049d4-00001e18-00000000-1d4ed58784102f9&deviceId=18900] [T1003 - Credential Dumping #2] [Group: sm-detection] [Device Email: smultani@carbonblack.com] [Device Name: win-559j1nqvfgj] [Device Type: WINDOWS] [IOC: b7e9fd8e-febe-478c-8f44-2e90e0d10507-0] [Severity: 10]', 'url': 'https://defense-eap01.conferdeploy.net', 'deviceInfo': {'deviceName': 'win-559j1nqvfgj', 'deviceHostName': '', 'externalIpAddress': '73.69.152.214', 'deviceId': 18900, 'uemId': '', 'targetPriorityCode': 0, 'internalIpAddress': '192.168.81.148', 'groupName': 'sm-detection', 'deviceType': 'WINDOWS', 'deviceVersion': 'pscr-sensor', 'email': 'smultani@carbonblack.com', 'targetPriorityType': 'MEDIUM'}, 'source': 'test', 'ruleName': 'sm-sentinel-watchlist', 'threatHunterInfo': {'responseSeverity': 10, 'reportName': 'T1003 - Credential Dumping #2', 'documentGuid': 'qgp18td2TFK2Dw3YB2MuSA', 'runState': 'RAN', 'firstActivityTime': 1554651734686, 'dismissed': 'false', 'targetPriority': 'MEDIUM', 'score': 10, 'indicators': [{'applicationName': 'mimikatz.exe', 'indicatorName': 'b7e9fd8e-febe-478c-8f44-2e90e0d10507-0', 'sha256Hash': '38ff9593dcd07b0252ed3f1ad34ce7b538c522fd2a4d6ffef00f73767e75edac'}], 'sha256': '38ff9593dcd07b0252ed3f1ad34ce7b538c522fd2a4d6ffef00f73767e75edac', 'status': 'UNRESOLVED', 'processPath': 'c:\\users\\smultani\\music\\mimikatz_trunk (1)\\d\\mimikatz.exe', 'tags': '', 'watchLists': [{'alert': 'true', 'id': '3ExgIixySwmbRuaXoxxKeA', 'name': 'Carbon Black Advanced Threats'}], 'time': 1554652062248, 'reportId': '1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507', 'responseAlarmId': 'WNEXFKQ7-000049d4-00001e18-00000000-1d4ed58784102f9-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507', 'iocId': 'b7e9fd8e-febe-478c-8f44-2e90e0d10507-0', 'md5': 'a3298b7614ff07f91301655edd58e9d7', 'count': 0, 'threatCause': {'actorProcessPPid': '', 'reason': 'Process mimikatz.exe was detected by the report "T1003 - Credential Dumping #2" in watchlist "Carbon Black Advanced Threats"', 'reputation': 'PUP', 'threatCategory': 'RESPONSE_WATCHLIST', 'actorName': 'mimikatz.exe', 'causeEventId': '', 'actorType': '', 'originSourceType': 'UNKNOWN', 'actor': '38ff9593dcd07b0252ed3f1ad34ce7b538c522fd2a4d6ffef00f73767e75edac'}, 'lastUpdatedTime': 0, 'threatId': '5f1763e2ea26c424e8a84ec6b1090983', 'summary': 'T1003 - Credential Dumping #2', 'reputation': 'PUP', 'orgId': 428, 'policyId': 9815, 'processGuid': 'WNEXFKQ7-000049d4-00001e18-00000000-1d4ed58784102f9', 'incidentId': 'WNEXFKQ7-000049d4-00001e18-00000000-1d4ed58784102f9-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507'}, 'type': 'THREAT_HUNTER'}, {'eventTime': 1554651550298, 'eventDescription': '[sm-sentinel-notification] [Carbon Black has detected a threat against your company.] [https://defense-eap01.conferdeploy.net#device/18900/incident/WNEXFKQ7-000049d4-00000954-00000000-1d4ed5809bf5af8-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507] [T1003 - Credential Dumping #2] [Incident id: WNEXFKQ7-000049d4-00000954-00000000-1d4ed5809bf5af8-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507] [Threat score: 10] [Group: sm-detection] [Email: smultani@carbonblack.com] [Name: win-559j1nqvfgj] [Type and OS: WINDOWS pscr-sensor] [Severity: 10]\n', 'url': 'https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-00000954-00000000-1d4ed5809bf5af8-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507', 'deviceInfo': {'deviceName': 'win-559j1nqvfgj', 'deviceHostName': '', 'externalIpAddress': '73.69.152.214', 'deviceId': 18900, 'uemId': '', 'targetPriorityCode': 0, 'internalIpAddress': '192.168.81.148', 'groupName': 'sm-detection', 'deviceType': 'WINDOWS', 'deviceVersion': 'pscr-sensor', 'email': 'smultani@carbonblack.com', 'targetPriorityType': 'MEDIUM'}, 'source': 'test', 'ruleName': 'sm-sentinel-notification', 'threatHunterInfo': {'responseSeverity': 10, 'reportName': 'T1003 - Credential Dumping #2', 'documentGuid': 'F-OinTckReGkfHVvNZqe1w', 'runState': 'RAN', 'firstActivityTime': 1554651550298, 'dismissed': 'false', 'targetPriority': 'MEDIUM', 'score': 10, 'indicators': [{'applicationName': 'mimikatz.exe', 'indicatorName': 'b7e9fd8e-febe-478c-8f44-2e90e0d10507-0', 'sha256Hash': '6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be'}], 'sha256': '6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be', 'status': 'UNRESOLVED', 'processPath': 'c:\\users\\smultani\\desktop\\mimikatz_trunk (1)\\win32\\mimikatz.exe', 'tags': '', 'watchLists': [{'alert': 'true', 'id': '3ExgIixySwmbRuaXoxxKeA', 'name': 'Carbon Black Advanced Threats'}], 'time': 1554652062265, 'reportId': '1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507', 'responseAlarmId': 'WNEXFKQ7-000049d4-00000954-00000000-1d4ed5809bf5af8-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507', 'iocId': 'b7e9fd8e-febe-478c-8f44-2e90e0d10507-0', 'md5': '9e9ea5e8a16995124ba6e75bad4c6abe', 'count': 0, 'threatCause': {'actorProcessPPid': '', 'reason': 'Process mimikatz.exe was detected by the report "T1003 - Credential Dumping #2" in watchlist "Carbon Black Advanced Threats"', 'reputation': 'KNOWN_MALWARE', 'threatCategory': 'RESPONSE_WATCHLIST', 'actorName': 'mimikatz.exe', 'causeEventId': '', 'actorType': '', 'originSourceType': 'UNKNOWN', 'actor': '6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be'}, 'lastUpdatedTime': 0, 'threatId': '5f1763e2ea26c424e8a84ec6b1090983', 'summary': 'T1003 - Credential Dumping #2', 'reputation': 'KNOWN_MALWARE', 'orgId': 428, 'policyId': 9815, 'processGuid': 'WNEXFKQ7-000049d4-00000954-00000000-1d4ed5809bf5af8', 'incidentId': 'WNEXFKQ7-000049d4-00000954-00000000-1d4ed5809bf5af8-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507'}, 'type': 'THREAT_HUNTER'}, {'eventTime': 1554651976107, 'eventDescription': '[sm-sentinel-notification] [Carbon Black has detected a threat against your company.] [https://defense-eap01.conferdeploy.net#device/18900/incident/WNEXFKQ7-000049d4-00000ac8-00000000-1d4ed590863aac9-n8JQkq8TuqkYoTiT5wObg-47a50561-e6ff-4106-8df1-5777f70a98d5] [Memory Grab using ProcDump] [Incident id: WNEXFKQ7-000049d4-00000ac8-00000000-1d4ed590863aac9-n8JQkq8TuqkYoTiT5wObg-47a50561-e6ff-4106-8df1-5777f70a98d5] [Threat score: 9] [Group: sm-detection] [Email: smultani@carbonblack.com] [Name: win-559j1nqvfgj] [Type and OS: WINDOWS pscr-sensor] [Severity: 9]\n', 'url': 'https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-00000ac8-00000000-1d4ed590863aac9-n8JQkq8TuqkYoTiT5wObg-47a50561-e6ff-4106-8df1-5777f70a98d5', 'deviceInfo': {'deviceName': 'win-559j1nqvfgj', 'deviceHostName': '', 'externalIpAddress': '73.69.152.214', 'deviceId': 18900, 'uemId': '', 'targetPriorityCode': 0, 'internalIpAddress': '192.168.81.148', 'groupName': 'sm-detection', 'deviceType': 'WINDOWS', 'deviceVersion': 'pscr-sensor', 'email': 'smultani@carbonblack.com', 'targetPriorityType': 'MEDIUM'}, 'source': 'test', 'ruleName': 'sm-sentinel-notification', 'threatHunterInfo': {'responseSeverity': 9, 'reportName': 'Memory Grab using ProcDump', 'documentGuid': 'L8UMm1dOR76_T6nBv-PBFw', 'runState': 'RAN', 'firstActivityTime': 1554651976107, 'dismissed': 'false', 'targetPriority': 'MEDIUM', 'score': 9, 'indicators': [{'applicationName': 'procdump64.exe', 'indicatorName': '47a50561-e6ff-4106-8df1-5777f70a98d5-0', 'sha256Hash': '16f413862efda3aba631d8a7ae2bfff6d84acd9f454a7adaa518c7a8a6f375a5'}], 'sha256': '16f413862efda3aba631d8a7ae2bfff6d84acd9f454a7adaa518c7a8a6f375a5', 'status': 'UNRESOLVED', 'processPath': 'c:\\users\\smultani\\downloads\\procdump\\procdump64.exe', 'tags': '', 'watchLists': [{'alert': 'true', 'id': 'JBeEYzBcQpSMXu3lWoSv8w', 'name': 'Carbon Black Community'}], 'time': 1554652418230, 'reportId': 'n8JQkq8TuqkYoTiT5wObg-47a50561-e6ff-4106-8df1-5777f70a98d5', 'responseAlarmId': 'WNEXFKQ7-000049d4-00000ac8-00000000-1d4ed590863aac9-n8JQkq8TuqkYoTiT5wObg-47a50561-e6ff-4106-8df1-5777f70a98d5', 'iocId': '47a50561-e6ff-4106-8df1-5777f70a98d5-0', 'md5': 'a92669ec8852230a10256ac23bbf4489', 'count': 0, 'threatCause': {'actorProcessPPid': '', 'reason': 'Process procdump64.exe was detected by the report "Memory Grab using ProcDump" in watchlist "Carbon Black Community"', 'reputation': 'TRUSTED_WHITE_LIST', 'threatCategory': 'RESPONSE_WATCHLIST', 'actorName': 'procdump64.exe', 'causeEventId': '', 'actorType': '', 'originSourceType': 'UNKNOWN', 'actor': '16f413862efda3aba631d8a7ae2bfff6d84acd9f454a7adaa518c7a8a6f375a5'}, 'lastUpdatedTime': 0, 'threatId': 'db260acf65984a2c74ae0c41a8e08086', 'summary': 'Memory Grab using ProcDump', 'reputation': 'TRUSTED_WHITE_LIST', 'orgId': 428, 'policyId': 9815, 'processGuid': 'WNEXFKQ7-000049d4-00000ac8-00000000-1d4ed590863aac9', 'incidentId': 'WNEXFKQ7-000049d4-00000ac8-00000000-1d4ed590863aac9-n8JQkq8TuqkYoTiT5wObg-47a50561-e6ff-4106-8df1-5777f70a98d5'}, 'type': 'THREAT_HUNTER'}, {'eventTime': 1554651828170, 'eventDescription': '[sm-sentinel-notification] [Carbon Black has detected a threat against your company.] [https://defense-eap01.conferdeploy.net#device/18900/incident/WNEXFKQ7-000049d4-000011c4-00000000-1d4ed58af5a4ce9-1X7Zx5ZRbGc24xRp7IaQ-7aa6e57a-6fa8-423d-b997-427565bf7a06] [T1003 - Credential Dumping #3] [Incident id: WNEXFKQ7-000049d4-000011c4-00000000-1d4ed58af5a4ce9-1X7Zx5ZRbGc24xRp7IaQ-7aa6e57a-6fa8-423d-b997-427565bf7a06] [Threat score: 9] [Group: sm-detection] [Email: smultani@carbonblack.com] [Name: win-559j1nqvfgj] [Type and OS: WINDOWS pscr-sensor] [Severity: 9]\n', 'url': 'https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-000011c4-00000000-1d4ed58af5a4ce9-1X7Zx5ZRbGc24xRp7IaQ-7aa6e57a-6fa8-423d-b997-427565bf7a06', 'deviceInfo': {'deviceName': 'win-559j1nqvfgj', 'deviceHostName': '', 'externalIpAddress': '73.69.152.214', 'deviceId': 18900, 'uemId': '', 'targetPriorityCode': 0, 'internalIpAddress': '192.168.81.148', 'groupName': 'sm-detection', 'deviceType': 'WINDOWS', 'deviceVersion': 'pscr-sensor', 'email': 'smultani@carbonblack.com', 'targetPriorityType': 'MEDIUM'}, 'source': 'test', 'ruleName': 'sm-sentinel-notification', 'threatHunterInfo': {'responseSeverity': 9, 'reportName': 'T1003 - Credential Dumping #3', 'documentGuid': 'NM1Pn_drQ3airxKooRokmQ', 'runState': 'RAN', 'firstActivityTime': 1554651828170, 'dismissed': 'false', 'targetPriority': 'MEDIUM', 'score': 9, 'indicators': [{'applicationName': 'procdump.exe', 'indicatorName': '7aa6e57a-6fa8-423d-b997-427565bf7a06-0', 'sha256Hash': '05732e84de58a3cc142535431b3aa04efbe034cc96e837f93c360a6387d8faad'}], 'sha256': '05732e84de58a3cc142535431b3aa04efbe034cc96e837f93c360a6387d8faad', 'status': 'UNRESOLVED', 'processPath': 'c:\\users\\smultani\\downloads\\procdump\\procdump.exe', 'tags': '', 'watchLists': [{'alert': 'true', 'id': '3ExgIixySwmbRuaXoxxKeA', 'name': 'Carbon Black Advanced Threats'}], 'time': 1554652418279, 'reportId': '1X7Zx5ZRbGc24xRp7IaQ-7aa6e57a-6fa8-423d-b997-427565bf7a06', 'responseAlarmId': 'WNEXFKQ7-000049d4-000011c4-00000000-1d4ed58af5a4ce9-1X7Zx5ZRbGc24xRp7IaQ-7aa6e57a-6fa8-423d-b997-427565bf7a06', 'iocId': '7aa6e57a-6fa8-423d-b997-427565bf7a06-0', 'md5': '6a09bc6c19c4236c0bd8a01953371a29', 'count': 0, 'threatCause': {'actorProcessPPid': '', 'reason': 'Process procdump.exe was detected by the report "T1003 - Credential Dumping #3" in watchlist "Carbon Black Advanced Threats"', 'reputation': 'TRUSTED_WHITE_LIST', 'threatCategory': 'RESPONSE_WATCHLIST', 'actorName': 'procdump.exe', 'causeEventId': '', 'actorType': '', 'originSourceType': 'UNKNOWN', 'actor': '05732e84de58a3cc142535431b3aa04efbe034cc96e837f93c360a6387d8faad'}, 'lastUpdatedTime': 0, 'threatId': 'ddb41379ce092f02c635851f4a9364f2', 'summary': 'T1003 - Credential Dumping #3', 'reputation': 'TRUSTED_WHITE_LIST', 'orgId': 428, 'policyId': 9815, 'processGuid': 'WNEXFKQ7-000049d4-000011c4-00000000-1d4ed58af5a4ce9', 'incidentId': 'WNEXFKQ7-000049d4-000011c4-00000000-1d4ed58af5a4ce9-1X7Zx5ZRbGc24xRp7IaQ-7aa6e57a-6fa8-423d-b997-427565bf7a06'}, 'type': 'THREAT_HUNTER'}, {'eventTime': 1554651837865, 'eventDescription': '[sm-sentinel-notification] [Carbon Black has detected a threat against your company.] [https://defense-eap01.conferdeploy.net#device/18900/incident/WNEXFKQ7-000049d4-00001228-00000000-1d4ed58b5502502-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507] [T1003 - Credential Dumping #2] [Incident id: WNEXFKQ7-000049d4-00001228-00000000-1d4ed58b5502502-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507] [Threat score: 10] [Group: sm-detection] [Email: smultani@carbonblack.com] [Name: win-559j1nqvfgj] [Type and OS: WINDOWS pscr-sensor] [Severity: 10]\n', 'url': 'https://defense-eap01.conferdeploy.net/investigate?s[searchWindow]=ALL&s[c][DEVICE_ID][0]=18900&s[c][INCIDENT_ID][0]=WNEXFKQ7-000049d4-00001228-00000000-1d4ed58b5502502-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507', 'deviceInfo': {'deviceName': 'win-559j1nqvfgj', 'deviceHostName': '', 'externalIpAddress': '73.69.152.214', 'deviceId': 18900, 'uemId': '', 'targetPriorityCode': 0, 'internalIpAddress': '192.168.81.148', 'groupName': 'sm-detection', 'deviceType': 'WINDOWS', 'deviceVersion': 'pscr-sensor', 'email': 'smultani@carbonblack.com', 'targetPriorityType': 'MEDIUM'}, 'source': 'test', 'ruleName': 'sm-sentinel-notification', 'threatHunterInfo': {'responseSeverity': 10, 'reportName': 'T1003 - Credential Dumping #2', 'documentGuid': 'FtA0ybjVRJuJ2VohA5E-Lw', 'runState': 'RAN', 'firstActivityTime': 1554651837865, 'dismissed': 'false', 'targetPriority': 'MEDIUM', 'score': 10, 'indicators': [{'applicationName': 'mimikatz.exe', 'indicatorName': 'b7e9fd8e-febe-478c-8f44-2e90e0d10507-0', 'sha256Hash': '6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be'}], 'sha256': '6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be', 'status': 'UNRESOLVED', 'processPath': 'c:\\users\\smultani\\music\\mimikatz_trunk (1)\\win32\\mimikatz.exe', 'tags': '', 'watchLists': [{'alert': 'true', 'id': '3ExgIixySwmbRuaXoxxKeA', 'name': 'Carbon Black Advanced Threats'}], 'time': 1554652418305, 'reportId': '1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507', 'responseAlarmId': 'WNEXFKQ7-000049d4-00001228-00000000-1d4ed58b5502502-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507', 'iocId': 'b7e9fd8e-febe-478c-8f44-2e90e0d10507-0', 'md5': '9e9ea5e8a16995124ba6e75bad4c6abe', 'count': 0, 'threatCause': {'actorProcessPPid': '', 'reason': 'Process mimikatz.exe was detected by the report "T1003 - Credential Dumping #2" in watchlist "Carbon Black Advanced Threats"', 'reputation': 'KNOWN_MALWARE', 'threatCategory': 'RESPONSE_WATCHLIST', 'actorName': 'mimikatz.exe', 'causeEventId': '', 'actorType': '', 'originSourceType': 'UNKNOWN', 'actor': '6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be'}, 'lastUpdatedTime': 0, 'threatId': '5f1763e2ea26c424e8a84ec6b1090983', 'summary': 'T1003 - Credential Dumping #2', 'reputation': 'KNOWN_MALWARE', 'orgId': 428, 'policyId': 9815, 'processGuid': 'WNEXFKQ7-000049d4-00001228-00000000-1d4ed58b5502502', 'incidentId': 'WNEXFKQ7-000049d4-00001228-00000000-1d4ed58b5502502-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507'}, 'type': 'THREAT_HUNTER'}, {'eventTime': 1554651837865, 'eventDescription': '[sm-sentinel-watchlist] [Carbon Black has detected one or more threat indicator(s) on one of your devices.] [https://defense-eap01.conferdeploy.net/threat-hunter/analyze?processGUID=WNEXFKQ7-000049d4-00001228-00000000-1d4ed58b5502502&deviceId=18900] [T1003 - Credential Dumping #2] [Group: sm-detection] [Device Email: smultani@carbonblack.com] [Device Name: win-559j1nqvfgj] [Device Type: WINDOWS] [IOC: b7e9fd8e-febe-478c-8f44-2e90e0d10507-0] [Severity: 10]', 'url': 'https://defense-eap01.conferdeploy.net', 'deviceInfo': {'deviceName': 'win-559j1nqvfgj', 'deviceHostName': '', 'externalIpAddress': '73.69.152.214', 'deviceId': 18900, 'uemId': '', 'targetPriorityCode': 0, 'internalIpAddress': '192.168.81.148', 'groupName': 'sm-detection', 'deviceType': 'WINDOWS', 'deviceVersion': 'pscr-sensor', 'email': 'smultani@carbonblack.com', 'targetPriorityType': 'MEDIUM'}, 'source': 'test', 'ruleName': 'sm-sentinel-watchlist', 'threatHunterInfo': {'responseSeverity': 10, 'reportName': 'T1003 - Credential Dumping #2', 'documentGuid': 'FtA0ybjVRJuJ2VohA5E-Lw', 'runState': 'RAN', 'firstActivityTime': 1554651837865, 'dismissed': 'false', 'targetPriority': 'MEDIUM', 'score': 10, 'indicators': [{'applicationName': 'mimikatz.exe', 'indicatorName': 'b7e9fd8e-febe-478c-8f44-2e90e0d10507-0', 'sha256Hash': '6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be'}], 'sha256': '6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be', 'status': 'UNRESOLVED', 'processPath': 'c:\\users\\smultani\\music\\mimikatz_trunk (1)\\win32\\mimikatz.exe', 'tags': '', 'watchLists': [{'alert': 'true', 'id': '3ExgIixySwmbRuaXoxxKeA', 'name': 'Carbon Black Advanced Threats'}], 'time': 1554652418330, 'reportId': '1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507', 'responseAlarmId': 'WNEXFKQ7-000049d4-00001228-00000000-1d4ed58b5502502-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507', 'iocId': 'b7e9fd8e-febe-478c-8f44-2e90e0d10507-0', 'md5': '9e9ea5e8a16995124ba6e75bad4c6abe', 'count': 0, 'threatCause': {'actorProcessPPid': '', 'reason': 'Process mimikatz.exe was detected by the report "T1003 - Credential Dumping #2" in watchlist "Carbon Black Advanced Threats"', 'reputation': 'KNOWN_MALWARE', 'threatCategory': 'RESPONSE_WATCHLIST', 'actorName': 'mimikatz.exe', 'causeEventId': '', 'actorType': '', 'originSourceType': 'UNKNOWN', 'actor': '6a127f8940419938d7aab6e99c85c46d80d273f25e064583771da346aa64b7be'}, 'lastUpdatedTime': 0, 'threatId': '5f1763e2ea26c424e8a84ec6b1090983', 'summary': 'T1003 - Credential Dumping #2', 'reputation': 'KNOWN_MALWARE', 'orgId': 428, 'policyId': 9815, 'processGuid': 'WNEXFKQ7-000049d4-00001228-00000000-1d4ed58b5502502', 'incidentId': 'WNEXFKQ7-000049d4-00001228-00000000-1d4ed58b5502502-1X7Zx5ZRbGc24xRp7IaQ-b7e9fd8e-febe-478c-8f44-2e90e0d10507'}, 'type': 'THREAT_HUNTER'}]

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null

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11

2f1ce7ff4fe3f25433c5b83ad3b58f9cb989dde1

21,000

py

Python

emulator/src/devices/cpu/arcompact/arcompact_make.py

rjw57/tiw-computer

5ef1c79893165b8622d1114d81cd0cded58910f0

[ "MIT" ]

1

2022-01-15T21:38:38.000Z

emulator/src/devices/cpu/arcompact/arcompact_make.py

rjw57/tiw-computer

5ef1c79893165b8622d1114d81cd0cded58910f0

[ "MIT" ]

null

emulator/src/devices/cpu/arcompact/arcompact_make.py

rjw57/tiw-computer

5ef1c79893165b8622d1114d81cd0cded58910f0

[ "MIT" ]

null

#!/usr/bin/python # license:BSD-3-Clause # copyright-holders:David Haywood from __future__ import print_function import sys def EmitGroup04_Handle_NZ_Flags(f, funcname, opname): print(" if (result & 0x80000000) { STATUS32_SET_N; }", file=f) print(" else { STATUS32_CLEAR_N; }", file=f) print(" if (result == 0x00000000) { STATUS32_SET_Z; }", file=f) print(" else { STATUS32_CLEAR_Z; }", file=f) def EmitGroup04_Handle_NZC_LSR1_Flags(f, funcname, opname): print(" if (result & 0x80000000) { STATUS32_SET_N; }", file=f) print(" else { STATUS32_CLEAR_N; }", file=f) print(" if (result == 0x00000000) { STATUS32_SET_Z; }", file=f) print(" else { STATUS32_CLEAR_Z; }", file=f) print(" if (c == 0x00000001) { STATUS32_SET_C; }", file=f) print(" else { STATUS32_CLEAR_C; }", file=f) def EmitGroup04_Handle_NZCV_ADD_Flags(f, funcname, opname): print(" if (result & 0x80000000) { STATUS32_SET_N; }", file=f) print(" else { STATUS32_CLEAR_N; }", file=f) print(" if (result == 0x00000000) { STATUS32_SET_Z; }", file=f) print(" else { STATUS32_CLEAR_Z; }", file=f) print(" if ((b & 0x80000000) == (c & 0x80000000))", file=f) print(" {", file=f) print(" if ((result & 0x80000000) != (b & 0x80000000))", file=f) print(" {", file=f) print(" STATUS32_SET_V;", file=f) print(" }", file=f) print(" else", file=f) print(" {", file=f) print(" STATUS32_CLEAR_V;", file=f) print(" }", file=f) print(" }", file=f) print(" if (b < c)", file=f) print(" {", file=f) print(" STATUS32_SET_C;", file=f) print(" }", file=f) print(" else", file=f) print(" {", file=f) print(" STATUS32_CLEAR_C;", file=f) print(" }", file=f) def EmitGroup04_no_Flags(f, funcname, opname): print(" // no flag changes", file=f) def EmitGroup04_unsupported_Flags(f, funcname, opname): print(" arcompact_fatal(\"arcompact_handle%s (%s) (F set)\\n\"); // not yet supported" % (funcname, opname), file=f) def EmitGroup04_Flaghandler(f,funcname, opname, flagcondition, flaghandler): if flagcondition == -1: print(" if (F)", file=f) print(" {", file=f) flaghandler(f, funcname, opname) print(" }", file=f) elif flagcondition == 0: print(" if (0)", file=f) print(" {", file=f) flaghandler(f, funcname, opname) print(" }", file=f) elif flagcondition == 1: print(" if (1)", file=f) print(" {", file=f) flaghandler(f, funcname, opname) print(" }", file=f) def EmitGroup04_u5fragment(f,funcname, opname, opexecute, opwrite, opwrite_alt, ignore_a, breg_is_dst_only, flagcondition, flaghandler): print(" int size = 4;", file=f) if breg_is_dst_only == 0: print(" uint32_t limm = 0;", file=f) print("/* int got_limm = 0; */", file=f) print(" ", file=f) print(" COMMON32_GET_breg;", file=f) if flagcondition == -1: print(" COMMON32_GET_F;", file=f) print(" COMMON32_GET_u6;", file=f) if ignore_a == 0: print(" COMMON32_GET_areg;", file=f) elif ignore_a == 1: print(" //COMMON32_GET_areg; // areg is reserved / not used", file=f) elif ignore_a == 2: print(" //COMMON32_GET_areg; // areg bits already used as opcode select", file=f) elif ignore_a == 3: print(" //COMMON32_GET_areg; // areg bits already used as condition code select", file=f) print(" ", file=f) print(" uint32_t c;", file=f) if breg_is_dst_only == 0: print(" uint32_t b;", file=f) print(" ", file=f) print(" /* is having b as LIMM valid here? LIMM vs. fixed u6 value makes no sense */", file=f) print(" if (breg == LIMM_REG)", file=f) print(" {", file=f) print(" GET_LIMM_32;", file=f) print(" size = 8;", file=f) print("/* got_limm = 1; */", file=f) print(" b = limm;", file=f) print(" }", file=f) print(" else", file=f) print(" {", file=f) print(" b = m_regs[breg];", file=f) print(" }", file=f) print(" ", file=f) print(" c = u;", file=f) print(" ", file=f) print(" /* todo: if areg = LIMM then there is no result (but since that register can never be read, I guess it doesn't matter if we store it there anyway?) */", file=f) def EmitGroup04(f,funcname, opname, opexecute, opwrite, opwrite_alt, ignore_a, breg_is_dst_only, flagcondition, flaghandler): # the mode 0x00 handler print("ARCOMPACT_RETTYPE arcompact_device::arcompact_handle%s_p00(OPS_32)" % funcname, file=f) print("{", file=f) print(" int size = 4;", file=f) print(" uint32_t limm = 0;", file=f) print(" int got_limm = 0;", file=f) print(" ", file=f) print(" COMMON32_GET_breg;", file=f) if flagcondition == -1: print(" COMMON32_GET_F;", file=f) print(" COMMON32_GET_creg;", file=f) if ignore_a == 0: print(" COMMON32_GET_areg;", file=f) elif ignore_a == 1: print(" //COMMON32_GET_areg; // areg is reserved / not used", file=f) elif ignore_a == 2: print(" //COMMON32_GET_areg; // areg bits already used as opcode select", file=f) print(" ", file=f) print(" uint32_t c;", file=f) if breg_is_dst_only == 0: print(" uint32_t b;", file=f) print(" ", file=f) print(" if (breg == LIMM_REG)", file=f) print(" {", file=f) print(" GET_LIMM_32;", file=f) print(" size = 8;", file=f) print(" got_limm = 1;", file=f) print(" b = limm;", file=f) print(" }", file=f) print(" else", file=f) print(" {", file=f) print(" b = m_regs[breg];", file=f) print(" }", file=f) print(" ", file=f) print(" if (creg == LIMM_REG)", file=f) print(" {", file=f) print(" if (!got_limm)", file=f) print(" {", file=f) print(" GET_LIMM_32;", file=f) print(" size = 8;", file=f) print(" }", file=f) print(" c = limm;", file=f) print(" }", file=f) print(" else", file=f) print(" {", file=f) print(" c = m_regs[creg];", file=f) print(" }", file=f) print(" /* todo: is the limm, limm syntax valid? (it's pointless.) */", file=f) print(" /* todo: if areg = LIMM then there is no result (but since that register can never be read, I guess it doesn't matter if we store it there anyway?) */", file=f) print(" %s" % opexecute, file=f) print(" %s" % opwrite, file=f) print(" ", file=f) EmitGroup04_Flaghandler(f,funcname,opname,flagcondition,flaghandler) print(" return m_pc + (size >> 0);", file=f) print("}", file=f) print("", file=f) print("", file=f) # the mode 0x01 handler print("ARCOMPACT_RETTYPE arcompact_device::arcompact_handle%s_p01(OPS_32)" % funcname, file=f) print("{", file=f) EmitGroup04_u5fragment(f,funcname, opname, opexecute, opwrite, opwrite_alt, ignore_a, breg_is_dst_only, flagcondition, flaghandler) print(" %s" % opexecute, file=f) print(" %s" % opwrite, file=f) print(" ", file=f) EmitGroup04_Flaghandler(f,funcname,opname,flagcondition,flaghandler) print(" return m_pc + (size >> 0);", file=f) print("}", file=f) print("", file=f) print("", file=f) # the mode 0x10 handler print("ARCOMPACT_RETTYPE arcompact_device::arcompact_handle%s_p10(OPS_32)" % funcname, file=f) if ignore_a == 2: print("{", file=f) print(" int size = 4;", file=f) print(" arcompact_fatal(\"illegal arcompact_handle%s_p10 (ares bits already used as opcode select, can't be used as s12) (%s)\\n\");" % (funcname, opname), file=f) print(" return m_pc + (size >> 0);", file=f) print("}", file=f) else: print("{", file=f) print(" int size = 4;", file=f) if breg_is_dst_only == 0: print(" uint32_t limm = 0;", file=f) print("/* int got_limm = 0; */", file=f) print(" ", file=f) print(" COMMON32_GET_breg;", file=f) if flagcondition == -1: print(" COMMON32_GET_F;", file=f) print(" COMMON32_GET_s12;", file=f) # areg can't be used here, it's used for s12 bits print(" ", file=f) print(" uint32_t c;", file=f) if breg_is_dst_only == 0: print(" uint32_t b;", file=f) print(" ", file=f) print(" /* is having b as LIMM valid here? LIMM vs. fixed u6 value makes no sense */", file=f) print(" if (breg == LIMM_REG)", file=f) print(" {", file=f) print(" GET_LIMM_32;", file=f) print(" size = 8;", file=f) print("/* got_limm = 1; */", file=f) print(" b = limm;", file=f) print(" }", file=f) print(" else", file=f) print(" {", file=f) print(" b = m_regs[breg];", file=f) print(" }", file=f) print(" ", file=f) print(" c = (uint32_t)S;", file=f) print(" ", file=f) print(" /* todo: if areg = LIMM then there is no result (but since that register can never be read, I guess it doesn't matter if we store it there anyway?) */", file=f) print(" %s" % opexecute, file=f) print(" %s" % opwrite_alt, file=f) print(" ", file=f) EmitGroup04_Flaghandler(f,funcname,opname,flagcondition,flaghandler) print(" return m_pc + (size >> 0);", file=f) print("}", file=f) print("", file=f) print("", file=f) # the mode 0x11 m0 handler print("ARCOMPACT_RETTYPE arcompact_device::arcompact_handle%s_p11_m0(OPS_32)" % funcname, file=f) if ignore_a == 2: print("{", file=f) print(" int size = 4;", file=f) print(" arcompact_fatal(\"illegal arcompact_handle%s_p11_m0 (ares bits already used as opcode select, can't be used as Q condition) (%s)\\n\");" % (funcname, opname), file=f) print(" return m_pc + (size >> 0);", file=f) print("}", file=f) else: print("{", file=f) print(" int size = 4;", file=f) print(" arcompact_fatal(\"arcompact_handle%s_p11_m0 (%s)\\n\");" % (funcname, opname), file=f) print(" return m_pc + (size >> 0);", file=f) print("}", file=f) print("", file=f) print("", file=f) # the mode 0x11 m1 handler print("ARCOMPACT_RETTYPE arcompact_device::arcompact_handle%s_p11_m1(OPS_32)" % funcname, file=f) if ignore_a == 2: print("{", file=f) print(" int size = 4;", file=f) print(" arcompact_fatal(\"illegal arcompact_handle%s_p11_m1 (ares bits already used as opcode select, can't be used as Q condition) (%s)\\n\");" % (funcname, opname), file=f) print(" return m_pc + (size >> 0);", file=f) print("}", file=f) else: print("{", file=f) EmitGroup04_u5fragment(f,funcname, opname, opexecute, opwrite, opwrite_alt, 3, breg_is_dst_only, flagcondition, flaghandler) print(" COMMON32_GET_CONDITION;", file=f) print(" if (!check_condition(condition))", file=f) print(" return m_pc + (size>>0);", file=f) print("", file=f) print(" %s" % opexecute, file=f) print(" %s" % opwrite_alt, file=f) print(" ", file=f) EmitGroup04_Flaghandler(f,funcname,opname,flagcondition,flaghandler) print(" return m_pc + (size >> 0);", file=f) print("}", file=f) print("", file=f) print("", file=f) # xxx_S c, b, u3 format opcodes (note c is destination) def EmitGroup0d(f,funcname, opname, opexecute, opwrite): print("ARCOMPACT_RETTYPE arcompact_device::arcompact_handle%s(OPS_16)" % funcname, file=f) print("{", file=f) print(" int u, breg, creg;", file=f) print("", file=f) print(" COMMON16_GET_u3;", file=f) print(" COMMON16_GET_breg;", file=f) print(" COMMON16_GET_creg;", file=f) print("", file=f) print(" REG_16BIT_RANGE(breg);", file=f) print(" REG_16BIT_RANGE(creg);", file=f) print("", file=f) print(" %s" % opexecute, file=f) print(" %s" % opwrite, file=f) print("", file=f) print(" return m_pc + (2 >> 0);", file=f) print("}", file=f) print("", file=f) print("", file=f) # xxx_S b <- b,c format opcodes def EmitGroup0f(f,funcname, opname, opexecute, opwrite): print("ARCOMPACT_RETTYPE arcompact_device::arcompact_handle%s(OPS_16)"% funcname, file=f) print("{", file=f) print(" int breg, creg;", file=f) print("", file=f) print(" COMMON16_GET_breg;", file=f) print(" COMMON16_GET_creg;", file=f) print("", file=f) print(" REG_16BIT_RANGE(breg);", file=f) print(" REG_16BIT_RANGE(creg);", file=f) print("", file=f) print(" %s" % opexecute, file=f) print(" %s" % opwrite, file=f) print("", file=f) print(" return m_pc + (2 >> 0);", file=f) print("}", file=f) print("", file=f) print("", file=f) # xxx_S b, b, u5 format opcodes def EmitGroup17(f,funcname, opname, opexecute): print("ARCOMPACT_RETTYPE arcompact_device::arcompact_handle%s(OPS_16)" % funcname, file=f) print("{", file=f) print(" int breg, u;", file=f) print(" ", file=f) print(" COMMON16_GET_breg;", file=f) print(" COMMON16_GET_u5;", file=f) print(" ", file=f) print(" REG_16BIT_RANGE(breg);", file=f) print(" ", file=f) print(" %s" % opexecute, file=f) print(" ", file=f) print(" return m_pc + (2 >> 0);", file=f) print("}", file=f) print("", file=f) print("", file=f) try: f = open(sys.argv[1], "w") except Exception: err = sys.exc_info()[1] sys.stderr.write("cannot write file %s [%s]\n" % (sys.argv[1], err)) sys.exit(1) EmitGroup04(f, "04_00", "ADD", "uint32_t result = b + c;", "m_regs[areg] = result;", "m_regs[breg] = result;", 0,0, -1, EmitGroup04_Handle_NZCV_ADD_Flags ) EmitGroup04(f, "04_02", "SUB", "uint32_t result = b - c;", "m_regs[areg] = result;", "m_regs[breg] = result;", 0,0, -1, EmitGroup04_unsupported_Flags ) EmitGroup04(f, "04_04", "AND", "uint32_t result = b & c;", "if (areg != LIMM_REG) { m_regs[areg] = result; }", "if (breg != LIMM_REG) { m_regs[breg] = result; }", 0,0, -1, EmitGroup04_Handle_NZ_Flags ) EmitGroup04(f, "04_05", "OR", "uint32_t result = b | c;", "m_regs[areg] = result;", "m_regs[breg] = result;", 0,0, -1, EmitGroup04_unsupported_Flags ) EmitGroup04(f, "04_06", "BIC", "uint32_t result = b & (~c);", "m_regs[areg] = result;", "m_regs[breg] = result;", 0,0, -1, EmitGroup04_unsupported_Flags ) EmitGroup04(f, "04_07", "XOR", "uint32_t result = b ^ c;", "m_regs[areg] = result;", "m_regs[breg] = result;", 0,0, -1, EmitGroup04_unsupported_Flags ) EmitGroup04(f, "04_0a", "MOV", "uint32_t result = c;", "m_regs[breg] = result;", "m_regs[breg] = result;", 1,1, -1, EmitGroup04_Handle_NZ_Flags ) # special case, result always goes to breg EmitGroup04(f, "04_0e", "RSUB", "uint32_t result = c - b;", "m_regs[areg] = result;", "m_regs[breg] = result;", 0,0, -1, EmitGroup04_unsupported_Flags ) EmitGroup04(f, "04_0f", "BSET", "uint32_t result = b | (1 << (c & 0x1f));", "m_regs[areg] = result;", "m_regs[breg] = result;", 0,0, -1, EmitGroup04_unsupported_Flags ) EmitGroup04(f, "04_13", "BMSK", "uint32_t result = b & ((1<<(c+1))-1);", "m_regs[areg] = result;", "m_regs[breg] = result;", 0,0, -1, EmitGroup04_unsupported_Flags ) EmitGroup04(f, "04_14", "ADD1", "uint32_t result = b + (c << 1);", "m_regs[areg] = result;", "m_regs[breg] = result;", 0,0, -1, EmitGroup04_unsupported_Flags ) EmitGroup04(f, "04_15", "ADD2", "uint32_t result = b + (c << 2);", "m_regs[areg] = result;", "m_regs[breg] = result;", 0,0, -1, EmitGroup04_unsupported_Flags ) EmitGroup04(f, "04_16", "ADD3", "uint32_t result = b + (c << 3);", "m_regs[areg] = result;", "m_regs[breg] = result;", 0,0, -1, EmitGroup04_unsupported_Flags ) EmitGroup04(f, "04_17", "SUB1", "uint32_t result = b - (c << 1);", "m_regs[areg] = result;", "m_regs[breg] = result;", 0,0, -1, EmitGroup04_unsupported_Flags ) EmitGroup04(f, "04_18", "SUB2", "uint32_t result = b - (c << 2);", "m_regs[areg] = result;", "m_regs[breg] = result;", 0,0, -1, EmitGroup04_unsupported_Flags ) EmitGroup04(f, "04_19", "SUB3", "uint32_t result = b - (c << 3);", "m_regs[areg] = result;", "m_regs[breg] = result;", 0,0, -1, EmitGroup04_unsupported_Flags ) EmitGroup04(f, "04_2a", "LR", "m_regs[breg] = READAUX(c);", "", "", 1,1, -1, EmitGroup04_no_Flags ) # this can't be conditional (todo) EmitGroup04(f, "04_2b", "SR", "WRITEAUX(c,b);", "", "", 1,0, -1, EmitGroup04_no_Flags ) # this can't be conditional (todo) EmitGroup04(f, "05_00", "ASL", "uint32_t result = b << (c&0x1f);", "m_regs[areg] = result;", "m_regs[breg] = result;", 0,0, -1, EmitGroup04_unsupported_Flags ) EmitGroup04(f, "05_01", "LSR", "uint32_t result = b >> (c&0x1f);", "m_regs[areg] = result;", "m_regs[breg] = result;", 0,0, -1, EmitGroup04_unsupported_Flags ) # the 04_2f subgroup uses the same encoding, but the areg is already used as sub-opcode select, so any modes relying on areg bits for other reasons (sign, condition) (modes 10, 11m0, 11m1) are illegal. the destination is also breg not areg EmitGroup04(f, "04_2f_02", "LSR1", "uint32_t result = c >> 1;", "m_regs[breg] = result;","", 2,1, -1, EmitGroup04_Handle_NZC_LSR1_Flags ) # no alt handler (invalid path) EmitGroup04(f, "04_2f_03", "ROR", "int shift = 1; uint32_t mask = (1 << (shift)) - 1; mask <<= (32-shift); uint32_t result = ((c >> shift) & ~mask) | ((c << (32-shift)) & mask);", "m_regs[breg] = result;","", 2,1, -1, EmitGroup04_Handle_NZC_LSR1_Flags ) EmitGroup04(f, "04_2f_07", "EXTB", "uint32_t result = c & 0x000000ff;", "m_regs[breg] = result;","", 2,1, -1, EmitGroup04_unsupported_Flags ) # ^ EmitGroup04(f, "04_2f_08", "EXTW", "uint32_t result = c & 0x0000ffff;", "m_regs[breg] = result;","", 2,1, -1, EmitGroup04_unsupported_Flags ) # ^ # xxx_S c, b, u3 format opcodes (note c is destination) EmitGroup0d(f, "0d_00", "ADD_S", "uint32_t result = m_regs[breg] + u;", "m_regs[creg] = result;" ) EmitGroup0d(f, "0d_01", "SUB_S", "uint32_t result = m_regs[breg] - u;", "m_regs[creg] = result;" ) EmitGroup0d(f, "0d_02", "ASL_S", "uint32_t result = m_regs[breg] << u;", "m_regs[creg] = result;" ) # xxx_S b <- b,c format opcodes (or in some cases xxx_S b,c) EmitGroup0f(f, "0f_02", "SUB_S", "uint32_t result = m_regs[breg] - m_regs[creg];", "m_regs[breg] = result;" ) EmitGroup0f(f, "0f_04", "AND_S", "uint32_t result = m_regs[breg] & m_regs[creg];", "m_regs[breg] = result;" ) EmitGroup0f(f, "0f_05", "OR_S", "uint32_t result = m_regs[breg] | m_regs[creg];", "m_regs[breg] = result;" ) EmitGroup0f(f, "0f_07", "XOR_S", "uint32_t result = m_regs[breg] ^ m_regs[creg];", "m_regs[breg] = result;" ) EmitGroup0f(f, "0f_0f", "EXTB_S","uint32_t result = m_regs[creg] & 0x000000ff;", "m_regs[breg] = result;" ) EmitGroup0f(f, "0f_10", "EXTW_S","uint32_t result = m_regs[creg] & 0x0000ffff;", "m_regs[breg] = result;" ) EmitGroup0f(f, "0f_13", "NEG_S"," uint32_t result = 0 - m_regs[creg];", "m_regs[breg] = result;" ) EmitGroup0f(f, "0f_14", "ADD1_S"," uint32_t result = m_regs[breg] + (m_regs[creg] <<1);", "m_regs[breg] = result;" ) EmitGroup0f(f, "0f_15", "ADD2_S"," uint32_t result = m_regs[breg] + (m_regs[creg] <<2);", "m_regs[breg] = result;" ) EmitGroup0f(f, "0f_16", "ADD3_S"," uint32_t result = m_regs[breg] + (m_regs[creg] <<3);", "m_regs[breg] = result;" ) EmitGroup0f(f, "0f_19", "LSR_S", "uint32_t result = m_regs[breg] >> (m_regs[creg]&0x1f);","m_regs[breg] = result;" ) EmitGroup0f(f, "0f_1b", "ASL1_S","uint32_t result = m_regs[creg] << 1;", "m_regs[breg] = result;" ) # xxx_S b, b, u5 format opcodes EmitGroup17(f, "17_00", "ASL_S", "m_regs[breg] = m_regs[breg] << (u&0x1f);" ) EmitGroup17(f, "17_01", "LSR_S", "m_regs[breg] = m_regs[breg] >> (u&0x1f);" ) EmitGroup17(f, "17_02", "ASR_S", "int32_t temp = (int32_t)m_regs[breg]; m_regs[breg] = temp >> (u&0x1f); // treat it as a signed value, so sign extension occurs during shift" ) EmitGroup17(f, "17_03", "SUB_S", "m_regs[breg] = m_regs[breg] - u;" ) EmitGroup17(f, "17_04", "BSET_S", "m_regs[breg] = m_regs[breg] | (1 << (u & 0x1f));" ) EmitGroup17(f, "17_06", "BMSK_S", "m_regs[breg] = m_regs[breg] | ((1 << (u + 1)) - 1);" )

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2f3ccf63208efa6950c2bf8dbcbff45c3618e69b

4,368

py

Python

util.py

xiongxiaochu/neural-network

59fdd400d3b3977e29aad5354577a5f315a57809

[ "Apache-2.0" ]

null

util.py

xiongxiaochu/neural-network

59fdd400d3b3977e29aad5354577a5f315a57809

[ "Apache-2.0" ]

null

util.py

xiongxiaochu/neural-network

59fdd400d3b3977e29aad5354577a5f315a57809

[ "Apache-2.0" ]

null

import numpy as np import sys from rnn import * from read_dataset import * from LSTMtheano import * from RNNtheano import * from LSTM_neg import * def save_model_parameters_lstm(model, outfile): np.savez(outfile, Wi=model.Wi.get_value(), Ui=model.Ui.get_value(), Wf=model.Wf.get_value(), Uf=model.Uf.get_value(), Wo=model.Wo.get_value(), Uo=model.Uo.get_value(), Wc=model.Wc.get_value(), Uc=model.Uc.get_value(), User_vector=model.User_vector.get_value(), Poi_vector=model.Poi_vector.get_value()) print "Saved model parameters to %s." % outfile def load_model_parameters_lstm(path, modelClass=LSTMtheano): npzfile = np.load(path) Wi, Ui, Wf, Uf, Wo, Uo, Wc, Uc, User_vector, Poi_vector = npzfile["Wi"], npzfile["Ui"], npzfile["Wf"], npzfile[ "Uf"], npzfile["Wo"], npzfile["Uo"], npzfile["Wc"], npzfile["Uc"], npzfile["User_vector"], npzfile["Poi_vector"] hidden_dim = Wi.shape[0] print "Building model, model from %s with hidden_dim=%d " % (path, hidden_dim) sys.stdout.flush() num_user = read_gtd_users() num_poi = read_gtd_pois() model = modelClass(hidden_dim=hidden_dim, num_user=num_user, num_poi=num_poi) model.Wi.set_value(Wi) model.Ui.set_value(Ui) model.Wf.set_value(Wf) model.Uf.set_value(Uf) model.Wo.set_value(Wo) model.Uo.set_value(Uo) model.Wc.set_value(Wc) model.Uc.set_value(Uc) model.User_vector.set_value(User_vector) model.Poi_vector.set_value(Poi_vector) return model def save_model_parameters_rnn(model, outfile): np.savez(outfile, M=model.M.get_value(), C=model.C.get_value(), # b=model.b.get_value(), User_vector=model.User_vector.get_value(), Poi_vector=model.Poi_vector.get_value()) print "Saved model parameters to %s." % outfile def load_model_parameters_rnn(path, modelClass=RNN): npzfile = np.load(path) M, C, User_vector, Poi_vector = npzfile["M"], npzfile["C"], npzfile["User_vector"], npzfile["Poi_vector"] hidden_dim = M.shape[0] user_dim = User_vector.shape[0] poi_dim = Poi_vector.shape[0] print "Building model, model from %s with hidden_dim=%d " % (path, hidden_dim) sys.stdout.flush() num_user = read_gtd_users() num_poi = read_gtd_pois() model = modelClass(user_dim=user_dim, poi_dim=poi_dim, hidden_dim=hidden_dim, num_user=num_user, num_poi=num_poi) model.M.set_value(M) model.C.set_value(C) model.User_vector.set_value(User_vector) model.Poi_vector.set_value(Poi_vector) return model def load_model_parameters_rnn1(path, modelClass=RNNtheano): npzfile = np.load(path) M, C, User_vector, Poi_vector = npzfile["M"], npzfile["C"], npzfile["User_vector"], npzfile["Poi_vector"] hidden_dim = M.shape[0] user_dim = User_vector.shape[0] poi_dim = Poi_vector.shape[0] print "Building model, model from %s with hidden_dim=%d " % (path, hidden_dim) sys.stdout.flush() num_user = read_foursquare_users() num_poi = read_foursquare_pois() model = modelClass(user_dim=user_dim, poi_dim=poi_dim, hidden_dim=hidden_dim, num_user=num_user, num_poi=num_poi) model.M.set_value(M) model.C.set_value(C) model.User_vector.set_value(User_vector) model.Poi_vector.set_value(Poi_vector) return model def load_model_parameters_lstm1(path, modelClass=LSTM_neg): npzfile = np.load(path) Wi, Ui, Wf, Uf, Wo, Uo, Wc, Uc, User_vector, Poi_vector = npzfile["Wi"], npzfile["Ui"], npzfile["Wf"], npzfile[ "Uf"], npzfile["Wo"], npzfile["Uo"], npzfile["Wc"], npzfile["Uc"], npzfile["User_vector"], npzfile["Poi_vector"] hidden_dim = Wi.shape[0] print "Building model, model from %s with hidden_dim=%d " % (path, hidden_dim) sys.stdout.flush() num_user = read_gtd_users() num_poi = read_gtd_pois() model = modelClass(hidden_dim=hidden_dim, num_user=num_user, num_poi=num_poi) model.Wi.set_value(Wi) model.Ui.set_value(Ui) model.Wf.set_value(Wf) model.Uf.set_value(Uf) model.Wo.set_value(Wo) model.Uo.set_value(Uo) model.Wc.set_value(Wc) model.Uc.set_value(Uc) model.User_vector.set_value(User_vector) model.Poi_vector.set_value(Poi_vector) return model

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8

2f9c48fbb63918179bee90b19b5cb086f30638fe

12,892

py

Python

startup/users/30-Harward.py

mrakitin/profile_collection-smi

1eea45a3b886b2c0daeec715ce94f27da24d0ba3

[ "BSD-3-Clause" ]

null

startup/users/30-Harward.py

mrakitin/profile_collection-smi

1eea45a3b886b2c0daeec715ce94f27da24d0ba3

[ "BSD-3-Clause" ]

null

startup/users/30-Harward.py

mrakitin/profile_collection-smi

1eea45a3b886b2c0daeec715ce94f27da24d0ba3

[ "BSD-3-Clause" ]

null

####line scan def run_harv_temp(tim=0.5): # Slowest cycle: temperatures = [25] name = 'ML' x_list = [-7000, 6000] y_list = [4900, 5100] samples = ['set7_sample1_3rdcycle', 'set7_sample2_3rdcycle'] assert len(x_list) == len(y_list), f'Number of X coordinates ({len(x_list)}) is different from number of Y coordinates ({len(y_list)})' assert len(x_list) == len(samples), f'Number of X coordinates ({len(x_list)}) is different from number of samples ({len(samples)})' #Detectors, motors: dets = [pil1M, pil300KW] #ALL detectors #dets = [pil300KW,ls.ch1_read, xbpm3.sumY] # WAXS detector ALONE x_offset = [0, 0, 400, 400] y_offset = [0, 50, 0, 50] zoff = -9000 waxs_arc = np.linspace(0, 32.5, 6) name_fmt = '{sample}_pos{offset}_{temperature}C_wa{waxs}' yield from bps.mv(piezo.z, zoff) det_exposure_time(tim, tim) for i_t, t in enumerate(temperatures): yield from bps.mv(ls.ch1_sp, t) if i_t !=0: yield from bps.sleep(600) temp = ls.ch1_read.value for j, wa in enumerate(waxs_arc): # yield from bps.mv(waxs, wa) for x, y, s in zip(x_list, y_list, samples): yield from bps.mv(piezo.x, x) yield from bps.mv(piezo.y, y) for i_0, (x_0, y_0) in enumerate(zip(x_offset, y_offset)): sample_name = name_fmt.format(sample=s, offset = i_0+1, temperature='%3.1f'%temp, waxs='%2.1f'%wa) yield from bps.mv(piezo.x, x+x_0) yield from bps.mv(piezo.y, y+y_0) print(f'\n\t=== Sample: {sample_name} ===\n') sample_id(user_name=name, sample_name=sample_name) yield from bp.count(dets, num=1) sample_id(user_name='test', sample_name='test') det_exposure_time(0.5,0.5) yield from bps.mv(ls.ch1_sp, 28) def run_harv_temp_all(tim=0.5): # Slowest cycle: temperatures = [100, 150] name = 'ML' #x_list = [-46300, -37300, -29800, -20300, -13800, -6200, 1300, 9000, 16700, 26300, 33300, 39300, 46300, 53000] #y_list = [-8800, -8800, -8800, -8750, -8750, -8750, -9200, -9200, -9300, -9100, -9200, -9300, -8970, -9000] #samples = [ 'set1_sample1', 'set1_sample2','set1_sample3','set1_sample4','set1_sample5', 'set1_sample6', 'set3_sample1', 'set3_sample2','set3_sample3','set3_sample4','set3_sample5', 'set3_sample6','set2_sample3', 'set2_sample4'] x_list = [42000, 28000, 13300, -7700, -14100] y_list = [-6800, -7800, -8800, -8800, -7800] samples = [ 'set6_headon_sample1', 'set6_headon_sample2','set6_headon_sample3','set6_headon_sample4','set6_headon_sample5'] assert len(x_list) == len(y_list), f'Number of X coordinates ({len(x_list)}) is different from number of Y coordinates ({len(y_list)})' assert len(x_list) == len(samples), f'Number of X coordinates ({len(x_list)}) is different from number of samples ({len(samples)})' #Detectors, motors: dets = [pil1M, pil300KW] #ALL detectors #dets = [pil300KW,ls.ch1_read, xbpm3.sumY] # WAXS detector ALONE x_offset = [0, 0, 400, 400] y_offset = [0, 50, 0, 50] zoff = -2000 waxs_arc = np.linspace(0, 32.5, 6) name_fmt = '{sample}_pos{offset}_{temperature}C_wa{waxs}' yield from bps.mv(piezo.z, zoff) det_exposure_time(tim, tim) for i_t, t in enumerate(temperatures): yield from bps.mv(ls.ch1_sp, t) if i_t !=0: yield from bps.sleep(600) temp = ls.ch1_read.value for j, wa in enumerate(waxs_arc): # yield from bps.mv(waxs, wa) for x, y, s in zip(x_list, y_list, samples): yield from bps.mv(piezo.x, x) yield from bps.mv(piezo.y, y) for i_0, (x_0, y_0) in enumerate(zip(x_offset, y_offset)): sample_name = name_fmt.format(sample=s, offset = i_0+1, temperature='%3.1f'%temp, waxs='%2.1f'%wa) yield from bps.mv(piezo.x, x+x_0) yield from bps.mv(piezo.y, y+y_0) print(f'\n\t=== Sample: {sample_name} ===\n') sample_id(user_name=name, sample_name=sample_name) yield from bp.count(dets, num=1) sample_id(user_name='test', sample_name='test') det_exposure_time(0.5,0.5) yield from bps.mv(ls.ch1_sp, 28) def run_harv_temp_linkam(tim=0.2): name = 'SL' sample = 'InSitu_EndOn_BDDA_5%_100C' #Detectors, motors: dets = [pil1M, pil300KW] waxs_arc = np.linspace(19.5 ,0 ,4) name_fmt = '{sample}_{temperature}C_wa{waxs}' #Openinig the gate valve yield from bps.mv(GV7.open_cmd, 1 ) yield from bps.sleep(5) yield from bps.mv(GV7.open_cmd, 1 ) yield from bps.sleep(5) det_exposure_time(tim, tim) temp = ls.ch1_read.value for j, wa in enumerate(waxs_arc): yield from bps.mv(waxs, wa) sample_name = name_fmt.format(sample=sample, temperature='%2.2f'%temp, waxs='%2.1f'%wa) print(f'\n\t=== Sample: {sample_name} ===\n') sample_id(user_name=name, sample_name=sample_name) yield from bp.count(dets, num=1) sample_id(user_name='test', sample_name='test') det_exposure_time(0.5,0.5) #Closing the gate valve yield from bps.mv(GV7.close_cmd, 1 ) yield from bps.sleep(5) yield from bps.mv(GV7.close_cmd, 1 ) yield from bps.sleep(5) def run_harv_temp_time(tim=0.2): name = 'SL' sample = 'InSitu_EndOn_NoCross_PhaseDia_40C_v3_UVlvl_0.5V' timegaps = [10]*4 + [30]*2 + [60]*3 #Detectors, motors: dets = [pil1M] waxs_arc = [19.5] name_fmt = '{sample}_{temperature}C_wa{waxs}' #Openinig the gate valve yield from bps.mv(GV7.open_cmd, 1 ) yield from bps.sleep(5) yield from bps.mv(GV7.open_cmd, 1 ) yield from bps.sleep(5) det_exposure_time(tim, tim) temp = ls.ch1_read.value for i, gap in enumerate(timegaps): sample = sample + '_timestep' + str(i) for j, wa in enumerate(waxs_arc): yield from bps.mv(waxs, wa) sample_name = name_fmt.format(sample=sample, temperature='%2.2f'%temp, waxs='%2.1f'%wa) print(f'\n\t=== Sample: {sample_name} ===\n') sample_id(user_name=name, sample_name=sample_name) yield from bp.count(dets, num=1) yield from bps.sleep(gap) for j, wa in enumerate(waxs_arc): yield from bps.mv(waxs, wa) sample_name = name_fmt.format(sample=sample, temperature='%2.2f'%temp, waxs='%2.1f'%wa) print(f'\n\t=== Sample: {sample_name} ===\n') sample_id(user_name=name, sample_name=sample_name) yield from bp.count(dets, num=1) sample_id(user_name='test', sample_name='test') det_exposure_time(0.5,0.5) #Closing the gate valve yield from bps.mv(GV7.close_cmd, 1 ) yield from bps.sleep(5) yield from bps.mv(GV7.close_cmd, 1 ) yield from bps.sleep(5) def harvphi(meas_t=0.5): waxs_arc = np.linspace(0, 32.5, 6) #(2th_min 2th_max steps) dets = [pil300KW, pil1M] names = ['DDDA5_vert_100C'] #phis = np.linspace(-90, 90, 13) phis = np.linspace(-75, 75, 11) for name in names: det_exposure_time(meas_t, meas_t) name_fmt = '{sample}_phi{phi}deg_wa{waxs}' #waxs is the slowest cycle: for j, wa in enumerate(waxs_arc): # yield from bps.mv(waxs, wa) #phi is scanned for a single waxs for i, phi in enumerate(phis): yield from bps.mv(prs, phi) sample_name = name_fmt.format(sample=name, phi = '%2.1f'%phi, waxs='%2.1f'%wa) sample_id(user_name='SL', sample_name=sample_name) print(f'\n\t=== Sample: {sample_name} ===\n') yield from bp.count(dets, num=1) yield from bps.mv(prs, 0) sample_id(user_name='test', sample_name='test') def run_harv_poly(tim=1,name = 'HarvPoly'): # Slowest cycle: temperatures = [85] x_list = [-1000 ] y_list = [-4740] samples = ['S29'] # Detectors, motors: dets = [pil300KW,ls.ch1_read, xbpm3.sumY] name_fmt = '{sample}_{temperature}C' assert len(x_list) == len(samples), f'Number of X coordinates ({len(x_list)}) is different from number of samples ({len(samples)})' det_exposure_time(tim, tim) for i_t, t in enumerate(temperatures): yield from bps.mv(ls.ch1_sp, t) #yield from bps.sleep(def run_harv_pos_scan(tim=3,name = 'Harv_SideOn_2.5_PA'): #x_list = [-42000, -20400, 200, 20400, 44300] x_list = np.linspace(-5800, -13800, 17) #y_list = [ 5600, 5800, 5920, 5822, 5972] y_list = [-4400] #Detectors, motors: #dets = [pil1M, rayonix, pil300KW,ls.ch1_read, xbpm3.sumY] #ALL detectors dets = [pil300KW,ls.ch1_read, xbpm3.sumY] # WAXS detector ALONE waxs_arc = [0, 30, 6] name_fmt = '{sample}_{xoffset}um_{temperature}C' # param = '16.1keV' det_exposure_time(tim, tim) yield from bps.mv(ls.ch1_sp, t) if i_t > 0: yield from bps.sleep(600) for x,y, s in zip(x_list, y_list, samples): temp = ls.ch1_read.value yield from bps.mv(piezo.x, x) yield from bps.mv(piezo.y, y) yield from bps.mv(piezo.z, 2800) for i_x, xo in enumerate(x_offset): sample_name = name_fmt.format(sample=s, xoffset = xo, temperature=temp) yield from bps.mv(piezo.x, x+x_offset[i_x]) print(f'\n\t=== Sample: {sample_name} ===\n') sample_id(user_name=name, sample_name=sample_name) yield from bp.rel_scan(dets, piezo.y, *y_range) sample_id(user_name='test', sample_name='test') def run_harv_micro(tim=3,name = 'HarvMicro_2_25C'): # Slowest cycle: temperatures = [150] #x_list = [-42000, -20400, 200, 20400, 44300] x_list = [40016, ] #y_list = [ 5600, 5800, 5920, 5822, 5972] y_list = [-3880, ] samples = [ 'SC10', 'SC11','SC12','SC13','SC14','SC15','SC16','SC17'] #samples = ['S29'] #Detectors, motors: #dets = [pil1M, rayonix, pil300KW,ls.ch1_read, xbpm3.sumY] #ALL detectors dets = [pil300KW,ls.ch1_read, xbpm3.sumY] # WAXS detector ALONE x_offset = [-704, -352, 0, 352, 704] y_range = [20, -20 , 3] waxs_arc = [0, 30, 6] name_fmt = '{sample}_{xoffset}um_{temperature}C' # param = '16.1keV' assert len(x_list) == len(samples), f'Number of X coordinates ({len(x_list)}) is different from number of samples ({len(samples)})' det_exposure_time(tim, tim) for i_t, t in enumerate(temperatures): yield from bps.mv(ls.ch1_sp, t) if i_t > 0: yield from bps.sleep(600) for x,y, s in zip(x_list, y_list, samples): temp = ls.ch1_read.value yield from bps.mv(piezo.x, x) yield from bps.mv(piezo.y, y) yield from bps.mv(piezo.z, 2800) for i_x, xo in enumerate(x_offset): sample_name = name_fmt.format(sample=s, xoffset = xo, temperature=temp) yield from bps.mv(piezo.x, x+x_offset[i_x]) print(f'\n\t=== Sample: {sample_name} ===\n') sample_id(user_name=name, sample_name=sample_name) yield from bp.rel_scan(dets, piezo.y, *y_range) sample_id(user_name='test', sample_name='test') det_exposure_time(0.5,0.5) yield from bps.mv(ls.ch1_sp, 28) def run_harv_pos(tim=5): # Slowest cycle: name = 'SL' x_list = [np.linspace(27700,28200, 26)] y_list = [-4400] samples = ['EndOn_1.5_HDDA_MicroStruct_Cap_Step20um_Area2'] assert len(x_list) == len(y_list), f'Number of X coordinates ({len(x_list)}) is different from number of Y coordinates ({len(y_list)})' assert len(x_list) == len(samples), f'Number of X coordinates ({len(x_list)}) is different from number of samples ({len(samples)})' #Detectors, motors: dets = [pil1M, pil300KW] #ALL detectors waxs_arc = [13] name_fmt = '{sample}_pos{offset}_wa{waxs}' det_exposure_time(tim, tim) for j, wa in enumerate(waxs_arc): # yield from bps.mv(waxs, wa) for x, y, s in zip(x_list, y_list, samples): yield from bps.mv(piezo.y, y) for i_0, x_0 in enumerate(x): yield from bps.mv(piezo.x, x_0) sample_name = name_fmt.format(sample=s, offset = i_0+1, waxs='%2.1f'%wa) print(f'\n\t=== Sample: {sample_name} ===\n') sample_id(user_name=name, sample_name=sample_name) yield from bp.count(dets, num=1) sample_id(user_name='test', sample_name='test') det_exposure_time(0.5,0.5) yield from bps.mv(ls.ch1_sp, 28)

40.413793

233

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0.038462

0

null

0

1

0

1

0

null

0

7

c80ace27ab3658dc7d55a162372973acf88641f1

51

py

Python

blast/None.py

lightsquared/overpressure

f0fee9085660d805a1574bb631548651ecf7c0fc

[ "Apache-2.0" ]

null

blast/None.py

lightsquared/overpressure

f0fee9085660d805a1574bb631548651ecf7c0fc

[ "Apache-2.0" ]

1

2022-02-26T06:58:09.000Z

blast/None.py

lightsquared/overpressure

f0fee9085660d805a1574bb631548651ecf7c0fc

[ "Apache-2.0" ]

null

# Cell add(1,3) # Cell add(1,3) # Cell add(1,3)

5.1

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null

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10

c07beee0262e3911f0a6bad02e15f8dad637a97c

21,644

py

Python

tests/test_indexing.py

Rubtsowa/dpnp

ef404c0f284b0c508ed1e556e140f02f76ae5551

[ "BSD-2-Clause" ]

37

2020-09-08T00:38:52.000Z

2022-03-18T01:44:10.000Z

tests/test_indexing.py

Rubtsowa/dpnp

ef404c0f284b0c508ed1e556e140f02f76ae5551

[ "BSD-2-Clause" ]

432

2020-09-07T09:48:41.000Z

2022-03-25T17:50:55.000Z

tests/test_indexing.py

Rubtsowa/dpnp

ef404c0f284b0c508ed1e556e140f02f76ae5551

[ "BSD-2-Clause" ]

17

2020-09-07T10:00:34.000Z

2022-03-25T13:53:43.000Z

import pytest import dpnp import numpy def test_choose(): a = numpy.r_[:4] ia = dpnp.array(a) b = numpy.r_[-4:0] ib = dpnp.array(b) c = numpy.r_[100:500:100] ic = dpnp.array(c) expected = numpy.choose([0, 0, 0, 0], [a, b, c]) result = dpnp.choose([0, 0, 0, 0], [ia, ib, ic]) numpy.testing.assert_array_equal(expected, result) @pytest.mark.parametrize("offset", [0, 1], ids=['0', '1']) @pytest.mark.parametrize("array", [[[0, 0], [0, 0]], [[1, 2], [1, 2]], [[1, 2], [3, 4]], [[0, 1, 2], [3, 4, 5], [6, 7, 8]], [[0, 1, 2, 3, 4], [5, 6, 7, 8, 9]], [[[1, 2], [3, 4]], [[1, 2], [2, 1]], [[1, 3], [3, 1]]], [[[[1, 2], [3, 4]], [[1, 2], [2, 1]]], [[[1, 3], [3, 1]], [[0, 1], [1, 3]]]], [[[[1, 2, 3], [3, 4, 5]], [[1, 2, 3], [2, 1, 0]]], [ [[1, 3, 5], [3, 1, 0]], [[0, 1, 2], [1, 3, 4]]]], [[[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]], [[[13, 14, 15], [16, 17, 18]], [[19, 20, 21], [22, 23, 24]]]]], ids=['[[0, 0], [0, 0]]', '[[1, 2], [1, 2]]', '[[1, 2], [3, 4]]', '[[0, 1, 2], [3, 4, 5], [6, 7, 8]]', '[[0, 1, 2, 3, 4], [5, 6, 7, 8, 9]]', '[[[1, 2], [3, 4]], [[1, 2], [2, 1]], [[1, 3], [3, 1]]]', '[[[[1, 2], [3, 4]], [[1, 2], [2, 1]]], [[[1, 3], [3, 1]], [[0, 1], [1, 3]]]]', '[[[[1, 2, 3], [3, 4, 5]], [[1, 2, 3], [2, 1, 0]]], [[[1, 3, 5], [3, 1, 0]], [[0, 1, 2], [1, 3, 4]]]]', '[[[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]], [[[13, 14, 15], [16, 17, 18]], [[19, 20, 21], [22, 23, 24]]]]']) def test_diagonal(array, offset): a = numpy.array(array) ia = dpnp.array(a) expected = numpy.diagonal(a, offset) result = dpnp.diagonal(ia, offset) numpy.testing.assert_array_equal(expected, result) @pytest.mark.parametrize("val", [-1, 0, 1], ids=['-1', '0', '1']) @pytest.mark.parametrize("array", [[[0, 0], [0, 0]], [[1, 2], [1, 2]], [[1, 2], [3, 4]], [[0, 1, 2], [3, 4, 5], [6, 7, 8]], [[0, 1, 2, 3, 4], [5, 6, 7, 8, 9]], [[[[1, 2], [3, 4]], [[1, 2], [2, 1]]], [[[1, 3], [3, 1]], [[0, 1], [1, 3]]]]], ids=['[[0, 0], [0, 0]]', '[[1, 2], [1, 2]]', '[[1, 2], [3, 4]]', '[[0, 1, 2], [3, 4, 5], [6, 7, 8]]', '[[0, 1, 2, 3, 4], [5, 6, 7, 8, 9]]', '[[[[1, 2], [3, 4]], [[1, 2], [2, 1]]], [[[1, 3], [3, 1]], [[0, 1], [1, 3]]]]']) def test_fill_diagonal(array, val): a = numpy.array(array) ia = dpnp.array(a) expected = numpy.fill_diagonal(a, val) result = dpnp.fill_diagonal(ia, val) numpy.testing.assert_array_equal(expected, result) @pytest.mark.parametrize("dimension", [(1, ), (2, ), (1, 2), (2, 3), (3, 2), [1], [2], [1, 2], [2, 3], [3, 2]], ids=['(1, )', '(2, )', '(1, 2)', '(2, 3)', '(3, 2)', '[1]', '[2]', '[1, 2]', '[2, 3]', '[3, 2]']) def test_indices(dimension): expected = numpy.indices(dimension) result = dpnp.indices(dimension) numpy.testing.assert_array_equal(expected, result) @pytest.mark.parametrize("array", [[], [[0, 0], [0, 0]], [[1, 0], [1, 0]], [[1, 2], [3, 4]], [[0, 1, 2], [3, 0, 5], [6, 7, 0]], [[0, 1, 0, 3, 0], [5, 0, 7, 0, 9]], [[[1, 2], [0, 4]], [[0, 2], [0, 1]], [[0, 0], [3, 1]]], [[[[1, 2, 3], [3, 4, 5]], [[1, 2, 3], [2, 1, 0]]], [ [[1, 3, 5], [3, 1, 0]], [[0, 1, 2], [1, 3, 4]]]]], ids=['[]', '[[0, 0], [0, 0]]', '[[1, 0], [1, 0]]', '[[1, 2], [3, 4]]', '[[0, 1, 2], [3, 0, 5], [6, 7, 0]]', '[[0, 1, 0, 3, 0], [5, 0, 7, 0, 9]]', '[[[1, 2], [0, 4]], [[0, 2], [0, 1]], [[0, 0], [3, 1]]]', '[[[[1, 2, 3], [3, 4, 5]], [[1, 2, 3], [2, 1, 0]]], [[[1, 3, 5], [3, 1, 0]], [[0, 1, 2], [1, 3, 4]]]]']) def test_nonzero(array): a = numpy.array(array) ia = dpnp.array(array) expected = numpy.nonzero(a) result = dpnp.nonzero(ia) numpy.testing.assert_array_equal(expected, result) @pytest.mark.parametrize("vals", [[100, 200], (100, 200)], ids=['[100, 200]', '(100, 200)']) @pytest.mark.parametrize("mask", [[[True, False], [False, True]], [[False, True], [True, False]], [[False, False], [True, True]]], ids=['[[True, False], [False, True]]', '[[False, True], [True, False]]', '[[False, False], [True, True]]']) @pytest.mark.parametrize("arr", [[[0, 0], [0, 0]], [[1, 2], [1, 2]], [[1, 2], [3, 4]]], ids=['[[0, 0], [0, 0]]', '[[1, 2], [1, 2]]', '[[1, 2], [3, 4]]']) def test_place1(arr, mask, vals): a = numpy.array(arr) ia = dpnp.array(a) m = numpy.array(mask) im = dpnp.array(m) numpy.place(a, m, vals) dpnp.place(ia, im, vals) numpy.testing.assert_array_equal(a, ia) @pytest.mark.parametrize("vals", [[100, 200], [100, 200, 300, 400, 500, 600], [100, 200, 300, 400, 500, 600, 800, 900]], ids=['[100, 200]', '[100, 200, 300, 400, 500, 600]', '[100, 200, 300, 400, 500, 600, 800, 900]']) @pytest.mark.parametrize("mask", [[[[True, False], [False, True]], [[False, True], [True, False]], [[False, False], [True, True]]]], ids=['[[[True, False], [False, True]], [[False, True], [True, False]], [[False, False], [True, True]]]']) @pytest.mark.parametrize("arr", [[[[1, 2], [3, 4]], [[1, 2], [2, 1]], [[1, 3], [3, 1]]]], ids=['[[[1, 2], [3, 4]], [[1, 2], [2, 1]], [[1, 3], [3, 1]]]']) def test_place2(arr, mask, vals): a = numpy.array(arr) ia = dpnp.array(a) m = numpy.array(mask) im = dpnp.array(m) numpy.place(a, m, vals) dpnp.place(ia, im, vals) numpy.testing.assert_array_equal(a, ia) @pytest.mark.parametrize("vals", [[100, 200], [100, 200, 300, 400, 500, 600], [100, 200, 300, 400, 500, 600, 800, 900]], ids=['[100, 200]', '[100, 200, 300, 400, 500, 600]', '[100, 200, 300, 400, 500, 600, 800, 900]']) @pytest.mark.parametrize("mask", [[[[[False, False], [True, True]], [[True, True], [True, True]]], [ [[False, False], [True, True]], [[False, False], [False, False]]]]], ids=['[[[[False, False], [True, True]], [[True, True], [True, True]]], [[[False, False], [True, True]], [[False, False], [False, False]]]]']) @pytest.mark.parametrize("arr", [[[[[1, 2], [3, 4]], [[1, 2], [2, 1]]], [[[1, 3], [3, 1]], [[0, 1], [1, 3]]]]], ids=['[[[[1, 2], [3, 4]], [[1, 2], [2, 1]]], [[[1, 3], [3, 1]], [[0, 1], [1, 3]]]]']) def test_place3(arr, mask, vals): a = numpy.array(arr) ia = dpnp.array(a) m = numpy.array(mask) im = dpnp.array(m) numpy.place(a, m, vals) dpnp.place(ia, im, vals) numpy.testing.assert_array_equal(a, ia) @pytest.mark.parametrize("v", [0, 1, 2, 3, 4], ids=['0', '1', '2', '3', '4']) @pytest.mark.parametrize("ind", [0, 1, 2, 3], ids=['0', '1', '2', '3']) @pytest.mark.parametrize("array", [[[0, 0], [0, 0]], [[1, 2], [1, 2]], [[1, 2], [3, 4]], [[[1, 2], [3, 4]], [[1, 2], [2, 1]], [[1, 3], [3, 1]]], [[[[1, 2], [3, 4]], [[1, 2], [2, 1]]], [[[1, 3], [3, 1]], [[0, 1], [1, 3]]]]], ids=['[[0, 0], [0, 0]]', '[[1, 2], [1, 2]]', '[[1, 2], [3, 4]]', '[[[1, 2], [3, 4]], [[1, 2], [2, 1]], [[1, 3], [3, 1]]]', '[[[[1, 2], [3, 4]], [[1, 2], [2, 1]]], [[[1, 3], [3, 1]], [[0, 1], [1, 3]]]]']) def test_put(array, ind, v): a = numpy.array(array) ia = dpnp.array(a) numpy.put(a, ind, v) dpnp.put(ia, ind, v) numpy.testing.assert_array_equal(a, ia) @pytest.mark.parametrize("v", [[10, 20], [30, 40]], ids=['[10, 20]', '[30, 40]']) @pytest.mark.parametrize("ind", [[0, 1], [2, 3]], ids=['[0, 1]', '[2, 3]']) @pytest.mark.parametrize("array", [[[0, 0], [0, 0]], [[1, 2], [1, 2]], [[1, 2], [3, 4]], [[[1, 2], [3, 4]], [[1, 2], [2, 1]], [[1, 3], [3, 1]]], [[[[1, 2], [3, 4]], [[1, 2], [2, 1]]], [[[1, 3], [3, 1]], [[0, 1], [1, 3]]]]], ids=['[[0, 0], [0, 0]]', '[[1, 2], [1, 2]]', '[[1, 2], [3, 4]]', '[[[1, 2], [3, 4]], [[1, 2], [2, 1]], [[1, 3], [3, 1]]]', '[[[[1, 2], [3, 4]], [[1, 2], [2, 1]]], [[[1, 3], [3, 1]], [[0, 1], [1, 3]]]]']) def test_put2(array, ind, v): a = numpy.array(array) ia = dpnp.array(a) numpy.put(a, ind, v) dpnp.put(ia, ind, v) numpy.testing.assert_array_equal(a, ia) def test_put3(): a = numpy.arange(5) ia = dpnp.array(a) dpnp.put(ia, [0, 2], [-44, -55]) numpy.put(a, [0, 2], [-44, -55]) numpy.testing.assert_array_equal(a, ia) def test_put_along_axis_val_int(): a = numpy.arange(16).reshape(4, 4) ai = dpnp.array(a) ind_r = numpy.array([[3, 0, 2, 1]]) ind_r_i = dpnp.array(ind_r) for axis in range(2): numpy.put_along_axis(a, ind_r, 777, axis) dpnp.put_along_axis(ai, ind_r_i, 777, axis) numpy.testing.assert_array_equal(a, ai) def test_put_along_axis1(): a = numpy.arange(64).reshape(4, 4, 4) ai = dpnp.array(a) ind_r = numpy.array([[[3, 0, 2, 1]]]) ind_r_i = dpnp.array(ind_r) for axis in range(3): numpy.put_along_axis(a, ind_r, 777, axis) dpnp.put_along_axis(ai, ind_r_i, 777, axis) numpy.testing.assert_array_equal(a, ai) def test_put_along_axis2(): a = numpy.arange(64).reshape(4, 4, 4) ai = dpnp.array(a) ind_r = numpy.array([[[3, 0, 2, 1]]]) ind_r_i = dpnp.array(ind_r) for axis in range(3): numpy.put_along_axis(a, ind_r, [100, 200, 300, 400], axis) dpnp.put_along_axis(ai, ind_r_i, [100, 200, 300, 400], axis) numpy.testing.assert_array_equal(a, ai) @pytest.mark.parametrize("vals", [[100, 200]], ids=['[100, 200]']) @pytest.mark.parametrize("mask", [[[True, False], [False, True]], [[False, True], [True, False]], [[False, False], [True, True]]], ids=['[[True, False], [False, True]]', '[[False, True], [True, False]]', '[[False, False], [True, True]]']) @pytest.mark.parametrize("arr", [[[0, 0], [0, 0]], [[1, 2], [1, 2]], [[1, 2], [3, 4]]], ids=['[[0, 0], [0, 0]]', '[[1, 2], [1, 2]]', '[[1, 2], [3, 4]]']) def test_putmask1(arr, mask, vals): a = numpy.array(arr) ia = dpnp.array(a) m = numpy.array(mask) im = dpnp.array(m) v = numpy.array(vals) iv = dpnp.array(v) numpy.putmask(a, m, v) dpnp.putmask(ia, im, iv) numpy.testing.assert_array_equal(a, ia) @pytest.mark.parametrize("vals", [[100, 200], [100, 200, 300, 400, 500, 600], [100, 200, 300, 400, 500, 600, 800, 900]], ids=['[100, 200]', '[100, 200, 300, 400, 500, 600]', '[100, 200, 300, 400, 500, 600, 800, 900]']) @pytest.mark.parametrize("mask", [[[[True, False], [False, True]], [[False, True], [True, False]], [[False, False], [True, True]]]], ids=['[[[True, False], [False, True]], [[False, True], [True, False]], [[False, False], [True, True]]]']) @pytest.mark.parametrize("arr", [[[[1, 2], [3, 4]], [[1, 2], [2, 1]], [[1, 3], [3, 1]]]], ids=['[[[1, 2], [3, 4]], [[1, 2], [2, 1]], [[1, 3], [3, 1]]]']) def test_putmask2(arr, mask, vals): a = numpy.array(arr) ia = dpnp.array(a) m = numpy.array(mask) im = dpnp.array(m) v = numpy.array(vals) iv = dpnp.array(v) numpy.putmask(a, m, v) dpnp.putmask(ia, im, iv) numpy.testing.assert_array_equal(a, ia) @pytest.mark.parametrize("vals", [[100, 200], [100, 200, 300, 400, 500, 600], [100, 200, 300, 400, 500, 600, 800, 900]], ids=['[100, 200]', '[100, 200, 300, 400, 500, 600]', '[100, 200, 300, 400, 500, 600, 800, 900]']) @pytest.mark.parametrize("mask", [[[[[False, False], [True, True]], [[True, True], [True, True]]], [ [[False, False], [True, True]], [[False, False], [False, False]]]]], ids=['[[[[False, False], [True, True]], [[True, True], [True, True]]], [[[False, False], [True, True]], [[False, False], [False, False]]]]']) @pytest.mark.parametrize("arr", [[[[[1, 2], [3, 4]], [[1, 2], [2, 1]]], [[[1, 3], [3, 1]], [[0, 1], [1, 3]]]]], ids=['[[[[1, 2], [3, 4]], [[1, 2], [2, 1]]], [[[1, 3], [3, 1]], [[0, 1], [1, 3]]]]']) def test_putmask3(arr, mask, vals): a = numpy.array(arr) ia = dpnp.array(a) m = numpy.array(mask) im = dpnp.array(m) v = numpy.array(vals) iv = dpnp.array(v) numpy.putmask(a, m, v) dpnp.putmask(ia, im, iv) numpy.testing.assert_array_equal(a, ia) def test_select(): cond_val1 = numpy.array([True, True, True, False, False, False, False, False, False, False]) cond_val2 = numpy.array([False, False, False, False, False, True, True, True, True, True]) icond_val1 = dpnp.array(cond_val1) icond_val2 = dpnp.array(cond_val2) condlist = [cond_val1, cond_val2] icondlist = [icond_val1, icond_val2] choice_val1 = numpy.full(10, -2) choice_val2 = numpy.full(10, -1) ichoice_val1 = dpnp.array(choice_val1) ichoice_val2 = dpnp.array(choice_val2) choicelist = [choice_val1, choice_val2] ichoicelist = [ichoice_val1, ichoice_val2] expected = numpy.select(condlist, choicelist) result = dpnp.select(icondlist, ichoicelist) numpy.testing.assert_array_equal(expected, result) @pytest.mark.parametrize("indices", [[[0, 0], [0, 0]], [[1, 2], [1, 2]], [[1, 2], [3, 4]]], ids=['[[0, 0], [0, 0]]', '[[1, 2], [1, 2]]', '[[1, 2], [3, 4]]']) @pytest.mark.parametrize("array", [[[0, 1, 2], [3, 4, 5], [6, 7, 8]], [[0, 1, 2, 3, 4], [5, 6, 7, 8, 9]], [[[1, 2], [3, 4]], [[1, 2], [2, 1]], [[1, 3], [3, 1]]], [[[[1, 2], [3, 4]], [[1, 2], [2, 1]]], [[[1, 3], [3, 1]], [[0, 1], [1, 3]]]], [[[[1, 2, 3], [3, 4, 5]], [[1, 2, 3], [2, 1, 0]]], [ [[1, 3, 5], [3, 1, 0]], [[0, 1, 2], [1, 3, 4]]]], [[[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]], [[[13, 14, 15], [16, 17, 18]], [[19, 20, 21], [22, 23, 24]]]]], ids=['[[0, 1, 2], [3, 4, 5], [6, 7, 8]]', '[[0, 1, 2, 3, 4], [5, 6, 7, 8, 9]]', '[[[1, 2], [3, 4]], [[1, 2], [2, 1]], [[1, 3], [3, 1]]]', '[[[[1, 2], [3, 4]], [[1, 2], [2, 1]]], [[[1, 3], [3, 1]], [[0, 1], [1, 3]]]]', '[[[[1, 2, 3], [3, 4, 5]], [[1, 2, 3], [2, 1, 0]]], [[[1, 3, 5], [3, 1, 0]], [[0, 1, 2], [1, 3, 4]]]]', '[[[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]], [[[13, 14, 15], [16, 17, 18]], [[19, 20, 21], [22, 23, 24]]]]']) def test_take(array, indices): a = numpy.array(array) ind = numpy.array(indices) ia = dpnp.array(a) iind = dpnp.array(ind) expected = numpy.take(a, ind) result = dpnp.take(ia, iind) numpy.testing.assert_array_equal(expected, result) def test_take_along_axis(): a = numpy.arange(16).reshape(4, 4) ai = dpnp.array(a) ind_r = numpy.array([[3, 0, 2, 1]]) ind_r_i = dpnp.array(ind_r) for axis in range(2): expected = numpy.take_along_axis(a, ind_r, axis) result = dpnp.take_along_axis(ai, ind_r_i, axis) numpy.testing.assert_array_equal(expected, result) def test_take_along_axis1(): a = numpy.arange(64).reshape(4, 4, 4) ai = dpnp.array(a) ind_r = numpy.array([[[3, 0, 2, 1]]]) ind_r_i = dpnp.array(ind_r) for axis in range(3): expected = numpy.take_along_axis(a, ind_r, axis) result = dpnp.take_along_axis(ai, ind_r_i, axis) numpy.testing.assert_array_equal(expected, result) @pytest.mark.parametrize("m", [None, 0, 1, 2, 3, 4], ids=['None', '0', '1', '2', '3', '4']) @pytest.mark.parametrize("k", [0, 1, 2, 3, 4, 5], ids=['0', '1', '2', '3', '4', '5']) @pytest.mark.parametrize("n", [1, 2, 3, 4, 5, 6], ids=['1', '2', '3', '4', '5', '6']) def test_tril_indices(n, k, m): result = dpnp.tril_indices(n, k, m) expected = numpy.tril_indices(n, k, m) numpy.testing.assert_array_equal(expected, result) @pytest.mark.parametrize("k", [0, 1, 2, 3, 4, 5], ids=['0', '1', '2', '3', '4', '5']) @pytest.mark.parametrize("array", [[[0, 0], [0, 0]], [[1, 2], [1, 2]], [[1, 2], [3, 4]], ], ids=['[[0, 0], [0, 0]]', '[[1, 2], [1, 2]]', '[[1, 2], [3, 4]]']) def test_tril_indices_from(array, k): a = numpy.array(array) ia = dpnp.array(a) result = dpnp.tril_indices_from(ia, k) expected = numpy.tril_indices_from(a, k) numpy.testing.assert_array_equal(expected, result) @pytest.mark.parametrize("m", [None, 0, 1, 2, 3, 4], ids=['None', '0', '1', '2', '3', '4']) @pytest.mark.parametrize("k", [0, 1, 2, 3, 4, 5], ids=['0', '1', '2', '3', '4', '5']) @pytest.mark.parametrize("n", [1, 2, 3, 4, 5, 6], ids=['1', '2', '3', '4', '5', '6']) def test_triu_indices(n, k, m): result = dpnp.triu_indices(n, k, m) expected = numpy.triu_indices(n, k, m) numpy.testing.assert_array_equal(expected, result) @pytest.mark.parametrize("k", [0, 1, 2, 3, 4, 5], ids=['0', '1', '2', '3', '4', '5']) @pytest.mark.parametrize("array", [[[0, 0], [0, 0]], [[1, 2], [1, 2]], [[1, 2], [3, 4]], ], ids=['[[0, 0], [0, 0]]', '[[1, 2], [1, 2]]', '[[1, 2], [3, 4]]']) def test_triu_indices_from(array, k): a = numpy.array(array) ia = dpnp.array(a) result = dpnp.triu_indices_from(ia, k) expected = numpy.triu_indices_from(a, k) numpy.testing.assert_array_equal(expected, result)

43.813765

166

0.371604

2,821

21,644

2.785183

0.043247

0.044801

0.037419

0.040728

0.857579

0.842179

0.813924

0.803996

0.796487

0.785796

0

0.138666

0.38893

21,644

493

167

43.902637

0.455391

0

0.740909

0

0.070455

0.160414

0

0.056818

1

0.056818

false

0

0.006818

0

0.063636

0

null

0

1

0

1

0

1

0

null

0

8

c0b72b51d58cfed584d3e24552e8f38a2da75a49

54,095

py

Python

Crack.py

Mr-AtackerXD/Crack

248d7c61b212a7fb5fbce90fea386a84b5c58896

[ "Apache-2.0" ]

1

2021-04-28T19:13:26.000Z

Crack.py

Mr-AtackerXD/Crack

248d7c61b212a7fb5fbce90fea386a84b5c58896

[ "Apache-2.0" ]

null

Crack.py

Mr-AtackerXD/Crack

248d7c61b212a7fb5fbce90fea386a84b5c58896

[ "Apache-2.0" ]

null

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gquant/dataframe_flow/__init__.py

miguelangel/gQuant

0bb5e392ce703d58baaf60668006e9a1f71d64ce

[ "Apache-2.0" ]

2

2021-08-13T03:02:22.000Z

2022-03-13T15:00:01.000Z

gquant/dataframe_flow/__init__.py

miguelangel/gQuant

0bb5e392ce703d58baaf60668006e9a1f71d64ce

[ "Apache-2.0" ]

3

2020-10-06T16:07:34.000Z

2021-04-28T20:30:14.000Z

gquant/dataframe_flow/__init__.py

miguelangel/gQuant

0bb5e392ce703d58baaf60668006e9a1f71d64ce

[ "Apache-2.0" ]

null

from .node import * # noqa: F401,F403 from .workflow import * # noqa: F401,F403

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py

Python

src/tests/unit/fixtures/platform/mock_reputation_override.py

kphsugntuedutw/carbon-black-cloud-sdk-python

5277be067223bc3eda0348c57b2a0004fa70f3e9

[ "MIT" ]

24

2020-10-16T22:07:38.000Z

2022-03-24T14:58:03.000Z

src/tests/unit/fixtures/platform/mock_reputation_override.py

kphsugntuedutw/carbon-black-cloud-sdk-python

5277be067223bc3eda0348c57b2a0004fa70f3e9

[ "MIT" ]

63

2020-10-26T18:26:15.000Z

2022-03-31T17:31:02.000Z

src/tests/unit/fixtures/platform/mock_reputation_override.py

kphsugntuedutw/carbon-black-cloud-sdk-python

5277be067223bc3eda0348c57b2a0004fa70f3e9

[ "MIT" ]

10

2020-11-09T11:54:23.000Z

2022-03-24T20:44:00.000Z

"""Mock responses for Reputation Override queries.""" REPUTATION_OVERRIDE_SHA256_REQUEST = { "description": "An override for a sha256 hash", "override_list": "BLACK_LIST", "override_type": "SHA256", "sha256_hash": "af62e6b3d475879c4234fe7bd8ba67ff6544ce6510131a069aaac75aa92aee7a", "filename": "foo.exe" } REPUTATION_OVERRIDE_SHA256_RESPONSE = { "id": "e9410b754ea011ebbfd0db2585a41b07", "created_by": "example@example.com", "create_time": "2021-01-04T15:24:18.002Z", "description": "An override for a foo.exe", "override_list": "BLACK_LIST", "override_type": "SHA256", "sha256_hash": "af62e6b3d475879c4234fe7bd8ba67ff6544ce6510131a069aaac75aa92aee7a", "filename": "foo.exe" } REPUTATION_OVERRIDE_SHA256_SEARCH_RESPONSE = { "num_found": 1, "results": [ { "id": "e9410b754ea011ebbfd0db2585a41b07", "created_by": "example@example.com", "create_time": "2021-01-04T15:24:18.002Z", "description": "An override for a foo.exe", "override_list": "BLACK_LIST", "override_type": "SHA256", "sha256_hash": "af62e6b3d475879c4234fe7bd8ba67ff6544ce6510131a069aaac75aa92aee7a", "filename": "foo.exe" } ] }

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py

Python

set-up_PRIME.py

fvguilherme/Manjaro-stuffs

804e3de0bbd6081ce24cd0ad2ecb0e66c15cc990

[ "MIT" ]

null

set-up_PRIME.py

fvguilherme/Manjaro-stuffs

804e3de0bbd6081ce24cd0ad2ecb0e66c15cc990

[ "MIT" ]

null

set-up_PRIME.py

fvguilherme/Manjaro-stuffs

804e3de0bbd6081ce24cd0ad2ecb0e66c15cc990

[ "MIT" ]

null

# Descrição (PT-BR) # Este script é uma automatização do HowTo criado pelo @jonathon (https://forum.manjaro.org/u/jonathon), # um moderador do fórum oficial da distribuição linux Manjaro (https://forum.manjaro.org). Me reservo o direito de ter # cometido erros durante a criação no script, que possam causar problemas em sua máquina, sejam de hardware ou de software. # Utilize-o por sua conta e risco próprios. Então, caso encontre erros, reporte-os. Toda e qualquer contribuição é sempre # bem vinda. # Description (EN-US) # That script is an automatization of the HowTo created by @jonathon (https://forum.manjaro.org/u/jonathon), # a moderator of the official forum of the Manjaro Linux dsitribution (https://forum.manjaro.org). I reserve the right # to have made errors during script creation, which may cause problems on your machine, whether hardware or software. # Use it at your own risk. So, if you find errors, report them. Any and all contributions are always welcome. function espace { echo '' echo '============================================================' echo '' } function LightDM_XFCE { espace echo 'LightDM é o DM escolhido. Iniciando as operações necessárias...' espace espace echo 'Setando a fonte de saída de acordo com o seu DM (gerenciador de login).' espace sudo pacman -Syyu xorg-xrandr echo '#!/bin/sh xrandr --setprovideroutputsource modesetting NVIDIA-0 xrandr --auto' > /usr/local/bin/optimus.sh chmod a+rx /usr/local/bin/optimus.sh echo '' echo '# # General configuration # # start-default-seat = True to always start one seat if none are defined in the configuration # greeter-user = User to run greeter as # minimum-display-number = Minimum display number to use for X servers # minimum-vt = First VT to run displays on # lock-memory = True to prevent memory from being paged to disk # user-authority-in-system-dir = True if session authority should be in the system location # guest-account-script = Script to be run to setup guest account # logind-check-graphical = True to on start seats that are marked as graphical by logind # log-directory = Directory to log information to # run-directory = Directory to put running state in # cache-directory = Directory to cache to # sessions-directory = Directory to find sessions # remote-sessions-directory = Directory to find remote sessions # greeters-directory = Directory to find greeters # backup-logs = True to move add a .old suffix to old log files when opening new ones # dbus-service = True if LightDM provides a D-Bus service to control it # [LightDM] #start-default-seat=true #greeter-user=lightdm #minimum-display-number=0 #minimum-vt=7 # Setting this to a value < 7 implies security issues, see FS#46799 #lock-memory=true #user-authority-in-system-dir=false #guest-account-script=guest-account #logind-check-graphical=false #log-directory=/var/log/lightdm run-directory=/run/lightdm #cache-directory=/var/cache/lightdm #sessions-directory=/usr/share/lightdm/sessions:/usr/share/xsessions:/usr/share/wayland-sessions #remote-sessions-directory=/usr/share/lightdm/remote-sessions #greeters-directory=$XDG_DATA_DIRS/lightdm/greeters:$XDG_DATA_DIRS/xgreeters #backup-logs=true #dbus-service=true # # Seat configuration # # Seat configuration is matched against the seat name glob in the section, for example: # [Seat:*] matches all seats and is applied first. # [Seat:seat0] matches the seat named "seat0". # [Seat:seat-thin-client*] matches all seats that have names that start with "seat-thin-client". # # type = Seat type (local, xremote, unity) # pam-service = PAM service to use for login # pam-autologin-service = PAM service to use for autologin # pam-greeter-service = PAM service to use for greeters # xserver-backend = X backend to use (mir) # xserver-command = X server command to run (can also contain arguments e.g. X -special-option) # xmir-command = Xmir server command to run (can also contain arguments e.g. Xmir -special-option) # xserver-config = Config file to pass to X server # xserver-layout = Layout to pass to X server # xserver-allow-tcp = True if TCP/IP connections are allowed to this X server # xserver-share = True if the X server is shared for both greeter and session # xserver-hostname = Hostname of X server (only for type=xremote) # xserver-display-number = Display number of X server (only for type=xremote) # xdmcp-manager = XDMCP manager to connect to (implies xserver-allow-tcp=true) # xdmcp-port = XDMCP UDP/IP port to communicate on # xdmcp-key = Authentication key to use for XDM-AUTHENTICATION-1 (stored in keys.conf) # unity-compositor-command = Unity compositor command to run (can also contain arguments e.g. unity-system-compositor -special-option) # unity-compositor-timeout = Number of seconds to wait for compositor to start # greeter-session = Session to load for greeter # greeter-hide-users = True to hide the user list # greeter-allow-guest = True if the greeter should show a guest login option # greeter-show-manual-login = True if the greeter should offer a manual login option # greeter-show-remote-login = True if the greeter should offer a remote login option # user-session = Session to load for users # allow-user-switching = True if allowed to switch users # allow-guest = True if guest login is allowed # guest-session = Session to load for guests (overrides user-session) # session-wrapper = Wrapper script to run session with # greeter-wrapper = Wrapper script to run greeter with # guest-wrapper = Wrapper script to run guest sessions with # display-setup-script = Script to run when starting a greeter session (runs as root) # display-stopped-script = Script to run after stopping the display server (runs as root) # greeter-setup-script = Script to run when starting a greeter (runs as root) # session-setup-script = Script to run when starting a user session (runs as root) # session-cleanup-script = Script to run when quitting a user session (runs as root) # autologin-guest = True to log in as guest by default # autologin-user = User to log in with by default (overrides autologin-guest) # autologin-user-timeout = Number of seconds to wait before loading default user # autologin-session = Session to load for automatic login (overrides user-session) # autologin-in-background = True if autologin session should not be immediately activated # exit-on-failure = True if the daemon should exit if this seat fails # [Seat:*] #type=local #pam-service=lightdm #pam-autologin-service=lightdm-autologin #pam-greeter-service=lightdm-greeter #xserver-backend= #xserver-command=X #xmir-command=Xmir #xserver-config= #xserver-layout= #xserver-allow-tcp=false #xserver-share=true #xserver-hostname= #xserver-display-number= #xdmcp-manager= #xdmcp-port=177 #xdmcp-key= #unity-compositor-command=unity-system-compositor #unity-compositor-timeout=60 greeter-session=lightdm-gtk-greeter #greeter-hide-users=false #greeter-allow-guest=true #greeter-show-manual-login=false #greeter-show-remote-login=true user-session=xfce #allow-user-switching=true #allow-guest=true #guest-session= session-wrapper=/etc/lightdm/Xsession #greeter-wrapper= #guest-wrapper= #display-setup-script= #display-stopped-script= #greeter-setup-script= #session-setup-script= #session-cleanup-script= #autologin-guest=false #autologin-user= #autologin-user-timeout=0 #autologin-in-background=false #autologin-session= #exit-on-failure=false display-setup-script=/usr/local/bin/optimus.sh # # XDMCP Server configuration # # enabled = True if XDMCP connections should be allowed # port = UDP/IP port to listen for connections on # listen-address = Host/address to listen for XDMCP connections (use all addresses if not present) # key = Authentication key to use for XDM-AUTHENTICATION-1 or blank to not use authentication (stored in keys.conf) # hostname = Hostname to report to XDMCP clients (defaults to system hostname if unset) # # The authentication key is a 56 bit DES key specified in hex as 0xnnnnnnnnnnnnnn. Alternatively # it can be a word and the first 7 characters are used as the key. # [XDMCPServer] #enabled=false #port=177 #listen-address= #key= #hostname= # # VNC Server configuration # # enabled = True if VNC connections should be allowed # command = Command to run Xvnc server with # port = TCP/IP port to listen for connections on # listen-address = Host/address to listen for VNC connections (use all addresses if not present) # width = Width of display to use # height = Height of display to use # depth = Color depth of display to use # [VNCServer] #enabled=false #command=Xvnc #port=5900 #listen-address= #width=1024 #height=768 #depth=8' > /etc/lightdm/lightdm.conf espace echo 'Instalação finalizada! Reinicie a máquina. =)' espace } function LightDM_Cinnamon { espace echo 'LightDM é o DM escolhido. Iniciando as operações necessárias...' espace espace echo 'Setando a fonte de saída de acordo com o seu DM (gerenciador de login) e instalando o xorg-xrandr.' espace sudo pacman -Syyu xorg-xrandr echo '#!/bin/sh xrandr --setprovideroutputsource modesetting NVIDIA-0 xrandr --auto' > /usr/local/bin/optimus.sh chmod a+rx /usr/local/bin/optimus.sh echo '' echo ' [LightDM] #minimum-vt=7 # Setting this to a value < 7 implies security issues, see FS#46799 run-directory=/run/lightdm [Seat:*] greeter-session=lightdm-slick-greeter # General configuration # # start-default-seat = True to always start one seat if none are defined in the configuration # greeter-user = User to run greeter as # minimum-display-number = Minimum display number to use for X servers # minimum-vt = First VT to run displays on # lock-memory = True to prevent memory from being paged to disk # user-authority-in-system-dir = True if session authority should be in the system location # guest-account-script = Script to be run to setup guest account # logind-check-graphical = True to on start seats that are marked as graphical by logind # log-directory = Directory to log information to # run-directory = Directory to put running state in # cache-directory = Directory to cache to # sessions-directory = Directory to find sessions # remote-sessions-directory = Directory to find remote sessions # greeters-directory = Directory to find greeters # backup-logs = True to move add a .old suffix to old log files when opening new ones # dbus-service = True if LightDM provides a D-Bus service to control it # [LightDM] #start-default-seat=true #greeter-user=lightdm #minimum-display-number=0 #minimum-vt=7 # Setting this to a value < 7 implies security issues, see FS#46799 #lock-memory=true #user-authority-in-system-dir=false #guest-account-script=guest-account #logind-check-graphical=false #log-directory=/var/log/lightdm run-directory=/run/lightdm #cache-directory=/var/cache/lightdm #sessions-directory=/usr/share/lightdm/sessions:/usr/share/xsessions:/usr/share/wayland-sessions #remote-sessions-directory=/usr/share/lightdm/remote-sessions #greeters-directory=$XDG_DATA_DIRS/lightdm/greeters:$XDG_DATA_DIRS/xgreeters #backup-logs=true #dbus-service=true # # Seat configuration # # Seat configuration is matched against the seat name glob in the section, for example: # [Seat:*] matches all seats and is applied first. # [Seat:seat0] matches the seat named "seat0". # [Seat:seat-thin-client*] matches all seats that have names that start with "seat-thin-client". # # type = Seat type (local, xremote, unity) # pam-service = PAM service to use for login # pam-autologin-service = PAM service to use for autologin # pam-greeter-service = PAM service to use for greeters # xserver-backend = X backend to use (mir) # xserver-command = X server command to run (can also contain arguments e.g. X -special-option) # xmir-command = Xmir server command to run (can also contain arguments e.g. Xmir -special-option) # xserver-config = Config file to pass to X server # xserver-layout = Layout to pass to X server # xserver-allow-tcp = True if TCP/IP connections are allowed to this X server # xserver-share = True if the X server is shared for both greeter and session # xserver-hostname = Hostname of X server (only for type=xremote) # xserver-display-number = Display number of X server (only for type=xremote) # xdmcp-manager = XDMCP manager to connect to (implies xserver-allow-tcp=true) # xdmcp-port = XDMCP UDP/IP port to communicate on # xdmcp-key = Authentication key to use for XDM-AUTHENTICATION-1 (stored in keys.conf) # unity-compositor-command = Unity compositor command to run (can also contain arguments e.g. unity-system-compositor -special-option) # unity-compositor-timeout = Number of seconds to wait for compositor to start # greeter-session = Session to load for greeter # greeter-hide-users = True to hide the user list # greeter-allow-guest = True if the greeter should show a guest login option # greeter-show-manual-login = True if the greeter should offer a manual login option # greeter-show-remote-login = True if the greeter should offer a remote login option # user-session = Session to load for users # allow-user-switching = True if allowed to switch users # allow-guest = True if guest login is allowed # guest-session = Session to load for guests (overrides user-session) # session-wrapper = Wrapper script to run session with # greeter-wrapper = Wrapper script to run greeter with # guest-wrapper = Wrapper script to run guest sessions with # display-setup-script = Script to run when starting a greeter session (runs as root) # display-stopped-script = Script to run after stopping the display server (runs as root) # greeter-setup-script = Script to run when starting a greeter (runs as root) # session-setup-script = Script to run when starting a user session (runs as root) # session-cleanup-script = Script to run when quitting a user session (runs as root) # autologin-guest = True to log in as guest by default # autologin-user = User to log in with by default (overrides autologin-guest) # autologin-user-timeout = Number of seconds to wait before loading default user # autologin-session = Session to load for automatic login (overrides user-session) # autologin-in-background = True if autologin session should not be immediately activated # exit-on-failure = True if the daemon should exit if this seat fails # [Seat:*] #type=local #pam-service=lightdm #pam-autologin-service=lightdm-autologin #pam-greeter-service=lightdm-greeter #xserver-backend= #xserver-command=X #xmir-command=Xmir #xserver-config= #xserver-layout= #xserver-allow-tcp=false #xserver-share=true #xserver-hostname= #xserver-display-number= #xdmcp-manager= #xdmcp-port=177 #xdmcp-key= #unity-compositor-command=unity-system-compositor #unity-compositor-timeout=60 greeter-session=lightdm-slick-greeter #greeter-hide-users=false #greeter-allow-guest=true #greeter-show-manual-login=false #greeter-show-remote-login=true user-session=cinnamon #allow-user-switching=true #allow-guest=true #guest-session= session-wrapper=/etc/lightdm/Xsession #greeter-wrapper= #guest-wrapper= #display-setup-script= #display-stopped-script= #greeter-setup-script= #session-setup-script= #session-cleanup-script= #autologin-guest=false #autologin-user= #autologin-user-timeout=0 #autologin-in-background=false #autologin-session= #exit-on-failure=false display-setup-script=/usr/local/bin/optimus.sh # # XDMCP Server configuration # # enabled = True if XDMCP connections should be allowed # port = UDP/IP port to listen for connections on # listen-address = Host/address to listen for XDMCP connections (use all addresses if not present) # key = Authentication key to use for XDM-AUTHENTICATION-1 or blank to not use authentication (stored in keys.conf) # hostname = Hostname to report to XDMCP clients (defaults to system hostname if unset) # # The authentication key is a 56 bit DES key specified in hex as 0xnnnnnnnnnnnnnn. Alternatively # it can be a word and the first 7 characters are used as the key. # [XDMCPServer] #enabled=false #port=177 #listen-address= #key= #hostname= # # VNC Server configuration # # enabled = True if VNC connections should be allowed # command = Command to run Xvnc server with # port = TCP/IP port to listen for connections on # listen-address = Host/address to listen for VNC connections (use all addresses if not present) # width = Width of display to use # height = Height of display to use # depth = Color depth of display to use # [VNCServer] #enabled=false #command=Xvnc #port=5900 #listen-address= #width=1024 #height=768 #depth=8 user-session=cinnamon session-wrapper=/etc/lightdm/Xsession #autologin-user= #autologin-user-timeout=0 #pam-autologin-service=lightdm-autologin' > /etc/lightdm/lightdm.conf espace echo 'Instalação finalizada! Reinicie a máquina. =)' espace } function GDM_GNOME { espace echo ' GDM é o DM escolhido. Iniciando as operações necessárias...' espace espace echo ' Setando a fonte de saída de acordo com o seu DM (gerenciador de login).' espace sudo echo '[Desktop Entry] Type=Application Name=Optimus Exec=/usr/local/bin/optimus.sh NoDisplay=true X-GNOME-Autostart-Phase=DisplayServer' > /usr/local/share/optimus.desktop echo '' echo ' Linkando o arquivo criado (/usr/local/share/optimus.desktop) para iniciar com o GDM.' echo '' sudo ln -s /usr/local/share/optimus.desktop /usr/share/gdm/greeter/autostart/optimus.desktop sudo ln -s /usr/local/share/optimus.desktop /etc/xdg/autostart/optimus.desktop echo '' espace echo ' Instalação finalizada! Reinicie a máquina. =)' espace } function SDDM_KDE { espace echo ' SDDM é o DM escolhido. Iniciando as operações necessárias...' espace espace echo ' Setando a fonte de saída de acordo com o seu DM (gerenciador de login).' espace sudo pacman -Syyu xorg-xrandr sudo echo 'xrandr --setprovideroutputsource modesetting NVIDIA-0 xrandr --auto' >> /usr/share/sddm/scripts/Xsetup chmod +x /usr/share/sddm/scripts/Xsetup echo '' espace echo ' Instalação finalizada! Reinicie a máquina. =)' espace } function commom { espace echo ' Iniciando a instalação do PRIME.' espace espace echo ' Removendo o Bumbleblee, caso esteja instalado.' espace sudo pacman -Rns bumblebee echo '' espace echo ' Instalando o driver da NVIDIA ("Fuck you! .i." by Torvalds =D).' espace sudo pacman -Syyu nvidia echo '' espace echo ' Setando uma nova configuração para o Xorg.' espace sudo echo 'Section "Module" Load "modesetting" EndSection Section "Device" Identifier "nvidia" Driver "nvidia" BusID "PCI:1:0:0" Option "AllowEmptyInitialConfiguration" Option "DPI" "96x96" Option "AllowIndirectGLXProtocol" "off" Option "TripleBuffer" "on" EndSection ' > /etc/X11/xorg.conf.d/optimus.conf echo '' espace echo ' Redefinindo a blacklist.' espace sudo rm /etc/modprobe.d/mhwd* echo '' sudo echo 'blacklist nouveau blacklist nvidiafb blacklist rivafb' > /etc/modprobe.d/nvidia.conf echo '' espace echo ' Ativando o nvidia-drm.modeset.' espace sudo echo 'options nvidia_drm modeset=1' > /etc/modprobe.d/nvidia-drm.conf echo '' espace echo ' Hora de escolher qual é o seu Display Manager (DM). PRESTE MUITA ATENÇÃO. Escolher o DM errado provavelmente implicará em tela preta após reiniciar.' espace } function DM_choice { espace echo 'Escolha o seu DM: 1 - LightDM (XFCE); 2 - LightDM (Cinnamon); 3 - GDM (GNOME); 4 - SDDM (KDE).' read OPT espace case $OPT in 1) LightDM_XFCE ;; 2) LightDM_Cinnamon ;; 3) GDM_GNOME ;; 4) SDDM_KDE ;; *) echo "As opções são apenas 1, 2, 3 ou 4. Saindo..." && exit esac } function inicio { espace echo ' ATENÇÃO! Antes de prosseguir, verifique o BusID da sua placa dedicada (3D controller) com o comando *** lspci | grep -E "VGA|3D" ***. Se a saída for algo como 01:00.0, prossiga. Caso contrário, modifique o script (linha 482) com o valor do BusID correspodente a sua placa.' echo '' echo ' Este script instala a versão 430.xx do driver da NVIDIA (nvidia). Se a sua placa for da arquiterura Fermi, por exemplo, você deve utilizar o driver 390xx (nvidia-390xx). Veja a arquitetura da sua GPU aqui: https://nouveau.freedesktop.org/wiki/CodeNames/.' echo ' Além disso, certifique-se que seu sistema está atualizado executando o comando abaixo. sudo pacman -Syyu' espace echo ' Você verificou as instruções descritas acima? 1 - Sim, quero prosseguir. 2 - Não, vou fazê-lo. Resposta:' echo '' read inicio case $inicio in 1) commom && DM_choice ;; 2) exit ;; *) echo 'As opções são apenas 1 ou 2. Saindo...' && exit esac } inicio # Referências # [1] https://forum.manjaro.org/t/howto-set-up-prime-with-nvidia-proprietary-driver/40225 # [2] https://wiki.manjaro.org/index.php?title=Configure_NVIDIA_(non-free)_settings_and_load_them_on_Startup#Introduction # [3] https://wiki.archlinux.org/index.php/NVIDIA # [4] https://wiki.archlinux.org/index.php/Bumblebee # [5] https://wiki.archlinux.org/index.php/Intel

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0.788555

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null

0

1

0

7

9e290d6ed2b1d81b03688f19092d7fa667ef2693

334

py

Python

tests/data/pipelinejobs/pipelinejob/__init__.py

SD2E/python-datacatalog

51ab366639505fb6e8a14cd6b446de37080cd20d

[ "CNRI-Python" ]

null

tests/data/pipelinejobs/pipelinejob/__init__.py

SD2E/python-datacatalog

51ab366639505fb6e8a14cd6b446de37080cd20d

[ "CNRI-Python" ]

2

2019-07-25T15:39:04.000Z

2019-10-21T15:31:46.000Z

tests/data/pipelinejobs/pipelinejob/__init__.py

SD2E/python-datacatalog

51ab366639505fb6e8a14cd6b446de37080cd20d

[ "CNRI-Python" ]

1

2019-10-15T14:33:44.000Z

CASES = [('tacobot.json', '1070761d-1a7a-535e-b6d3-a1a728a249ce', True)] EVENTS = [('tacobot-run.json', '1070761d-1a7a-535e-b6d3-a1a728a249ce', True), ('tacobot-update.json', '1070761d-1a7a-535e-b6d3-a1a728a249ce', True), ('tacobot-finish.json', '1070761d-1a7a-535e-b6d3-a1a728a249ce', True)] from .files import get_jobs, get_events

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9e677bb314a9df1aad9f42e0af9ba57500dd5b90

79

py

Python

services/__init__.py

panla/celery_services

4913df58b7b2f5a7226e7c2c0637f86d25d6ac67

[ "MIT" ]

null

services/__init__.py

panla/celery_services

4913df58b7b2f5a7226e7c2c0637f86d25d6ac67

[ "MIT" ]

null

services/__init__.py

panla/celery_services

4913df58b7b2f5a7226e7c2c0637f86d25d6ac67

[ "MIT" ]

null

from .pay_services.task import pay from .timer_services.task import timer_task

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9e7902c37192df3c1a185dda9098dddd3c45df41

58,577

py

Python

cpdb/social_graph/tests/queries/test_social_graph_data_query.py

invinst/CPDBv2_backend

b4e96d620ff7a437500f525f7e911651e4a18ef9

[ "Apache-2.0" ]

25

2018-07-20T22:31:40.000Z

2021-07-15T16:58:41.000Z

cpdb/social_graph/tests/queries/test_social_graph_data_query.py

invinst/CPDBv2_backend

b4e96d620ff7a437500f525f7e911651e4a18ef9

[ "Apache-2.0" ]

13

2018-06-18T23:08:47.000Z

2022-02-10T07:38:25.000Z

cpdb/social_graph/tests/queries/test_social_graph_data_query.py

invinst/CPDBv2_backend

b4e96d620ff7a437500f525f7e911651e4a18ef9

[ "Apache-2.0" ]

6

2018-05-17T21:59:43.000Z

2020-11-17T00:30:26.000Z

import pytz from datetime import datetime from django.test import TestCase from robber import expect from data.factories import OfficerFactory, AllegationFactory, OfficerAllegationFactory from data.models import Officer from social_graph.queries import SocialGraphDataQuery class SocialGraphDataQueryTestCase(TestCase): def test_execute_default(self): officer_1 = OfficerFactory( id=8562, first_name='Jerome', last_name='Finnigan', complaint_percentile=1.1, civilian_allegation_percentile=1.1, internal_allegation_percentile=2.2, trr_percentile=3.3, ) officer_2 = OfficerFactory( id=8563, first_name='Edward', last_name='May', complaint_percentile=4.4, civilian_allegation_percentile=4.4, internal_allegation_percentile=5.5, trr_percentile=6.6, ) officer_3 = OfficerFactory( id=8564, first_name='Joe', last_name='Parker', complaint_percentile=7.7, civilian_allegation_percentile=7.7, internal_allegation_percentile=8.8, trr_percentile=9.9, ) allegation_1 = AllegationFactory( crid='123', is_officer_complaint=False, incident_date=datetime(2005, 12, 31, tzinfo=pytz.utc) ) allegation_2 = AllegationFactory( crid='456', is_officer_complaint=False, incident_date=datetime(2006, 12, 31, tzinfo=pytz.utc) ) allegation_3 = AllegationFactory( crid='789', is_officer_complaint=False, incident_date=datetime(2007, 12, 31, tzinfo=pytz.utc) ) OfficerAllegationFactory(id=1, officer=officer_1, allegation=allegation_1) OfficerAllegationFactory(id=2, officer=officer_2, allegation=allegation_1) OfficerAllegationFactory(id=3, officer=officer_3, allegation=allegation_1) OfficerAllegationFactory(id=4, officer=officer_1, allegation=allegation_2) OfficerAllegationFactory(id=5, officer=officer_2, allegation=allegation_2) OfficerAllegationFactory(id=6, officer=officer_3, allegation=allegation_2) OfficerAllegationFactory(id=7, officer=officer_1, allegation=allegation_3) OfficerAllegationFactory(id=8, officer=officer_2, allegation=allegation_3) expected_officers = [ { 'full_name': 'Edward May', 'id': 8563, 'percentile_allegation': '4.4000', 'percentile_allegation_civilian': '4.4000', 'percentile_allegation_internal': '5.5000', 'percentile_trr': '6.6000' }, { 'full_name': 'Jerome Finnigan', 'id': 8562, 'percentile_allegation': '1.1000', 'percentile_allegation_civilian': '1.1000', 'percentile_allegation_internal': '2.2000', 'percentile_trr': '3.3000' }, { 'full_name': 'Joe Parker', 'id': 8564, 'percentile_allegation': '7.7000', 'percentile_allegation_civilian': '7.7000', 'percentile_allegation_internal': '8.8000', 'percentile_trr': '9.9000' }, ] expected_list_event = ['2006-12-31', '2007-12-31'] expected_static_list_event = ['2007-12-31'] expected_coaccused_data = [ { 'officer_id_1': 8562, 'officer_id_2': 8563, 'incident_date': '2006-12-31', 'accussed_count': 2 }, { 'officer_id_1': 8562, 'officer_id_2': 8564, 'incident_date': '2006-12-31', 'accussed_count': 2 }, { 'officer_id_1': 8563, 'officer_id_2': 8564, 'incident_date': '2006-12-31', 'accussed_count': 2 }, { 'officer_id_1': 8562, 'officer_id_2': 8563, 'incident_date': '2007-12-31', 'accussed_count': 3 } ] expected_graph_data = { 'officers': expected_officers, 'coaccused_data': expected_coaccused_data, 'list_event': expected_list_event } expected_static_graph_data = { 'officers': expected_officers, 'coaccused_data': expected_coaccused_data, 'list_event': expected_static_list_event } officers = Officer.objects.filter( id__in=[officer.id for officer in [officer_1, officer_2, officer_3]] ) social_graph_data_query = SocialGraphDataQuery(officers) expect(social_graph_data_query.graph_data()).to.eq(expected_graph_data) expect(social_graph_data_query.graph_data(static=True)).to.eq(expected_static_graph_data) def test_graph_data_threshold_1_complaint_origin_is_civilian(self): officer_1 = OfficerFactory( id=8562, first_name='Jerome', last_name='Finnigan', complaint_percentile=1.1, civilian_allegation_percentile=1.1, internal_allegation_percentile=2.2, trr_percentile=3.3, ) officer_2 = OfficerFactory( id=8563, first_name='Edward', last_name='May', complaint_percentile=4.4, civilian_allegation_percentile=4.4, internal_allegation_percentile=5.5, trr_percentile=6.6, ) officer_3 = OfficerFactory( id=8564, first_name='Joe', last_name='Parker', complaint_percentile=7.7, civilian_allegation_percentile=7.7, internal_allegation_percentile=8.8, trr_percentile=9.9, ) allegation_1 = AllegationFactory( crid='123', is_officer_complaint=False, incident_date=datetime(2005, 12, 31, tzinfo=pytz.utc) ) allegation_2 = AllegationFactory( crid='456', is_officer_complaint=True, incident_date=datetime(2006, 12, 31, tzinfo=pytz.utc) ) allegation_3 = AllegationFactory( crid='789', is_officer_complaint=False, incident_date=datetime(2007, 12, 31, tzinfo=pytz.utc) ) OfficerAllegationFactory(id=1, officer=officer_1, allegation=allegation_1) OfficerAllegationFactory(id=2, officer=officer_2, allegation=allegation_1) OfficerAllegationFactory(id=3, officer=officer_1, allegation=allegation_2) OfficerAllegationFactory(id=4, officer=officer_2, allegation=allegation_2) OfficerAllegationFactory(id=5, officer=officer_1, allegation=allegation_3) OfficerAllegationFactory(id=6, officer=officer_2, allegation=allegation_3) OfficerAllegationFactory(id=7, officer=officer_3, allegation=allegation_3) expected_coaccused_data = [ { 'officer_id_1': 8562, 'officer_id_2': 8563, 'incident_date': '2005-12-31', 'accussed_count': 1 }, { 'officer_id_1': 8562, 'officer_id_2': 8563, 'incident_date': '2007-12-31', 'accussed_count': 2 }, { 'officer_id_1': 8562, 'officer_id_2': 8564, 'incident_date': '2007-12-31', 'accussed_count': 1 }, { 'officer_id_1': 8563, 'officer_id_2': 8564, 'incident_date': '2007-12-31', 'accussed_count': 1 }, ] expected_officers = [ { 'full_name': 'Edward May', 'id': 8563, 'percentile_allegation': '4.4000', 'percentile_allegation_civilian': '4.4000', 'percentile_allegation_internal': '5.5000', 'percentile_trr': '6.6000' }, { 'full_name': 'Jerome Finnigan', 'id': 8562, 'percentile_allegation': '1.1000', 'percentile_allegation_civilian': '1.1000', 'percentile_allegation_internal': '2.2000', 'percentile_trr': '3.3000' }, { 'full_name': 'Joe Parker', 'id': 8564, 'percentile_allegation': '7.7000', 'percentile_allegation_civilian': '7.7000', 'percentile_allegation_internal': '8.8000', 'percentile_trr': '9.9000' }, ] expected_list_event = ['2005-12-31', '2007-12-31'] expected_graph_data = { 'officers': expected_officers, 'coaccused_data': expected_coaccused_data, 'list_event': expected_list_event } officers = Officer.objects.filter( id__in=[officer.id for officer in [officer_1, officer_2, officer_3]] ) social_graph_data_query = SocialGraphDataQuery(officers, threshold=1) expect(social_graph_data_query.graph_data()).to.eq(expected_graph_data) def test_graph_data_threshold_3_complaint_origin_is_civilian(self): officer_1 = OfficerFactory( id=8562, first_name='Jerome', last_name='Finnigan', complaint_percentile=1.1, civilian_allegation_percentile=1.1, internal_allegation_percentile=2.2, trr_percentile=3.3, ) officer_2 = OfficerFactory( id=8563, first_name='Edward', last_name='May', complaint_percentile=4.4, civilian_allegation_percentile=4.4, internal_allegation_percentile=5.5, trr_percentile=6.6, ) officer_3 = OfficerFactory( id=8564, first_name='Joe', last_name='Parker', complaint_percentile=7.7, civilian_allegation_percentile=7.7, internal_allegation_percentile=8.8, trr_percentile=9.9, ) officer_4 = OfficerFactory( id=8565, first_name='John', last_name='Snow', complaint_percentile=10.10, civilian_allegation_percentile=10.10, internal_allegation_percentile=11.11, trr_percentile=12.12, ) officer_5 = OfficerFactory( id=8566, first_name='John', last_name='Sena', complaint_percentile=13.13, civilian_allegation_percentile=13.13, internal_allegation_percentile=14.14, trr_percentile=15.15, ) allegation_1 = AllegationFactory( crid='123', is_officer_complaint=False, incident_date=datetime(2005, 12, 31, tzinfo=pytz.utc) ) allegation_2 = AllegationFactory( crid='456', is_officer_complaint=False, incident_date=datetime(2006, 12, 31, tzinfo=pytz.utc) ) allegation_3 = AllegationFactory( crid='789', is_officer_complaint=False, incident_date=datetime(2007, 12, 31, tzinfo=pytz.utc) ) allegation_4 = AllegationFactory( crid='987', is_officer_complaint=False, incident_date=datetime(2008, 12, 31, tzinfo=pytz.utc) ) OfficerAllegationFactory(id=1, officer=officer_1, allegation=allegation_1) OfficerAllegationFactory(id=2, officer=officer_2, allegation=allegation_1) OfficerAllegationFactory(id=3, officer=officer_2, allegation=allegation_2) OfficerAllegationFactory(id=4, officer=officer_3, allegation=allegation_2) OfficerAllegationFactory(id=5, officer=officer_2, allegation=allegation_3) OfficerAllegationFactory(id=6, officer=officer_3, allegation=allegation_3) OfficerAllegationFactory(id=7, officer=officer_3, allegation=allegation_1) OfficerAllegationFactory(id=8, officer=officer_4, allegation=allegation_1) OfficerAllegationFactory(id=9, officer=officer_4, allegation=allegation_2) OfficerAllegationFactory(id=10, officer=officer_4, allegation=allegation_3) OfficerAllegationFactory(id=11, officer=officer_5, allegation=allegation_1) OfficerAllegationFactory(id=12, officer=officer_5, allegation=allegation_2) OfficerAllegationFactory(id=13, officer=officer_5, allegation=allegation_3) OfficerAllegationFactory(id=14, officer=officer_4, allegation=allegation_4) OfficerAllegationFactory(id=15, officer=officer_5, allegation=allegation_4) expected_coaccused_data = [ { 'officer_id_1': 8563, 'officer_id_2': 8564, 'incident_date': '2007-12-31', 'accussed_count': 3 }, { 'officer_id_1': 8563, 'officer_id_2': 8565, 'incident_date': '2007-12-31', 'accussed_count': 3 }, { 'officer_id_1': 8563, 'officer_id_2': 8566, 'incident_date': '2007-12-31', 'accussed_count': 3 }, { 'officer_id_1': 8564, 'officer_id_2': 8565, 'incident_date': '2007-12-31', 'accussed_count': 3 }, { 'officer_id_1': 8564, 'officer_id_2': 8566, 'incident_date': '2007-12-31', 'accussed_count': 3 }, { 'officer_id_1': 8565, 'officer_id_2': 8566, 'incident_date': '2007-12-31', 'accussed_count': 3 }, { 'officer_id_1': 8565, 'officer_id_2': 8566, 'incident_date': '2008-12-31', 'accussed_count': 4 }, ] expected_officers = [ { 'full_name': 'Edward May', 'id': 8563, 'percentile_allegation': '4.4000', 'percentile_allegation_civilian': '4.4000', 'percentile_allegation_internal': '5.5000', 'percentile_trr': '6.6000' }, { 'full_name': 'Jerome Finnigan', 'id': 8562, 'percentile_allegation': '1.1000', 'percentile_allegation_civilian': '1.1000', 'percentile_allegation_internal': '2.2000', 'percentile_trr': '3.3000' }, { 'full_name': 'Joe Parker', 'id': 8564, 'percentile_allegation': '7.7000', 'percentile_allegation_civilian': '7.7000', 'percentile_allegation_internal': '8.8000', 'percentile_trr': '9.9000' }, { 'full_name': 'John Sena', 'id': 8566, 'percentile_allegation': '13.1300', 'percentile_allegation_civilian': '13.1300', 'percentile_allegation_internal': '14.1400', 'percentile_trr': '15.1500' }, { 'full_name': 'John Snow', 'id': 8565, 'percentile_allegation': '10.1000', 'percentile_allegation_civilian': '10.1000', 'percentile_allegation_internal': '11.1100', 'percentile_trr': '12.1200' }, ] expected_list_event = ['2007-12-31', '2008-12-31'] expected_graph_data = { 'officers': expected_officers, 'coaccused_data': expected_coaccused_data, 'list_event': expected_list_event } officers = Officer.objects.filter( id__in=[officer.id for officer in [officer_1, officer_2, officer_3, officer_4, officer_5]] ) social_graph_data_query = SocialGraphDataQuery(officers, threshold=3) expect(social_graph_data_query.graph_data()).to.eq(expected_graph_data) def test_graph_data_threshold_1_complaint_origin_is_officer(self): officer_1 = OfficerFactory( id=8562, first_name='Jerome', last_name='Finnigan', complaint_percentile=1.1, civilian_allegation_percentile=1.1, internal_allegation_percentile=2.2, trr_percentile=3.3, ) officer_2 = OfficerFactory( id=8563, first_name='Edward', last_name='May', complaint_percentile=4.4, civilian_allegation_percentile=4.4, internal_allegation_percentile=5.5, trr_percentile=6.6, ) officer_3 = OfficerFactory( id=8564, first_name='Joe', last_name='Parker', complaint_percentile=7.7, civilian_allegation_percentile=7.7, internal_allegation_percentile=8.8, trr_percentile=9.9, ) allegation_1 = AllegationFactory( crid='123', is_officer_complaint=True, incident_date=datetime(2005, 12, 31, tzinfo=pytz.utc) ) allegation_2 = AllegationFactory( crid='456', is_officer_complaint=False, incident_date=datetime(2006, 12, 31, tzinfo=pytz.utc) ) allegation_3 = AllegationFactory( crid='789', is_officer_complaint=True, incident_date=datetime(2007, 12, 31, tzinfo=pytz.utc) ) OfficerAllegationFactory(id=1, officer=officer_1, allegation=allegation_1) OfficerAllegationFactory(id=2, officer=officer_2, allegation=allegation_1) OfficerAllegationFactory(id=3, officer=officer_1, allegation=allegation_2) OfficerAllegationFactory(id=4, officer=officer_2, allegation=allegation_2) OfficerAllegationFactory(id=5, officer=officer_1, allegation=allegation_3) OfficerAllegationFactory(id=6, officer=officer_2, allegation=allegation_3) OfficerAllegationFactory(id=7, officer=officer_3, allegation=allegation_3) expected_coaccused_data = [ { 'officer_id_1': 8562, 'officer_id_2': 8563, 'incident_date': '2005-12-31', 'accussed_count': 1 }, { 'officer_id_1': 8562, 'officer_id_2': 8563, 'incident_date': '2007-12-31', 'accussed_count': 2 }, { 'officer_id_1': 8562, 'officer_id_2': 8564, 'incident_date': '2007-12-31', 'accussed_count': 1 }, { 'officer_id_1': 8563, 'officer_id_2': 8564, 'incident_date': '2007-12-31', 'accussed_count': 1 }, ] expected_officers = [ { 'full_name': 'Edward May', 'id': 8563, 'percentile_allegation': '4.4000', 'percentile_allegation_civilian': '4.4000', 'percentile_allegation_internal': '5.5000', 'percentile_trr': '6.6000' }, { 'full_name': 'Jerome Finnigan', 'id': 8562, 'percentile_allegation': '1.1000', 'percentile_allegation_civilian': '1.1000', 'percentile_allegation_internal': '2.2000', 'percentile_trr': '3.3000' }, { 'full_name': 'Joe Parker', 'id': 8564, 'percentile_allegation': '7.7000', 'percentile_allegation_civilian': '7.7000', 'percentile_allegation_internal': '8.8000', 'percentile_trr': '9.9000' }, ] expected_list_event = ['2005-12-31', '2007-12-31'] expected_graph_data = { 'officers': expected_officers, 'coaccused_data': expected_coaccused_data, 'list_event': expected_list_event } officers = Officer.objects.filter( id__in=[officer.id for officer in [officer_1, officer_2, officer_3]] ) social_graph_data_query = SocialGraphDataQuery( officers, threshold=1, complaint_origin='OFFICER' ) expect(social_graph_data_query.graph_data()).to.eq(expected_graph_data) def test_graph_data_threshold_3_complaint_origin_is_officer(self): officer_1 = OfficerFactory( id=8562, first_name='Jerome', last_name='Finnigan', complaint_percentile=1.1, civilian_allegation_percentile=1.1, internal_allegation_percentile=2.2, trr_percentile=3.3, ) officer_2 = OfficerFactory( id=8563, first_name='Edward', last_name='May', complaint_percentile=4.4, civilian_allegation_percentile=4.4, internal_allegation_percentile=5.5, trr_percentile=6.6, ) officer_3 = OfficerFactory( id=8564, first_name='Joe', last_name='Parker', complaint_percentile=7.7, civilian_allegation_percentile=7.7, internal_allegation_percentile=8.8, trr_percentile=9.9, ) officer_4 = OfficerFactory( id=8565, first_name='John', last_name='Snow', complaint_percentile=10.10, civilian_allegation_percentile=10.10, internal_allegation_percentile=11.11, trr_percentile=12.12, ) officer_5 = OfficerFactory( id=8566, first_name='John', last_name='Sena', complaint_percentile=13.13, civilian_allegation_percentile=13.13, internal_allegation_percentile=14.14, trr_percentile=15.15, ) allegation_1 = AllegationFactory( crid='123', is_officer_complaint=True, incident_date=datetime(2005, 12, 31, tzinfo=pytz.utc) ) allegation_2 = AllegationFactory( crid='456', is_officer_complaint=True, incident_date=datetime(2006, 12, 31, tzinfo=pytz.utc) ) allegation_3 = AllegationFactory( crid='789', is_officer_complaint=True, incident_date=datetime(2007, 12, 31, tzinfo=pytz.utc) ) allegation_4 = AllegationFactory( crid='987', is_officer_complaint=False, incident_date=datetime(2008, 12, 31, tzinfo=pytz.utc) ) OfficerAllegationFactory(id=1, officer=officer_1, allegation=allegation_1) OfficerAllegationFactory(id=2, officer=officer_2, allegation=allegation_1) OfficerAllegationFactory(id=3, officer=officer_2, allegation=allegation_2) OfficerAllegationFactory(id=4, officer=officer_3, allegation=allegation_2) OfficerAllegationFactory(id=5, officer=officer_2, allegation=allegation_3) OfficerAllegationFactory(id=6, officer=officer_3, allegation=allegation_3) OfficerAllegationFactory(id=7, officer=officer_3, allegation=allegation_1) OfficerAllegationFactory(id=8, officer=officer_4, allegation=allegation_1) OfficerAllegationFactory(id=9, officer=officer_4, allegation=allegation_2) OfficerAllegationFactory(id=10, officer=officer_4, allegation=allegation_3) OfficerAllegationFactory(id=11, officer=officer_5, allegation=allegation_1) OfficerAllegationFactory(id=12, officer=officer_5, allegation=allegation_2) OfficerAllegationFactory(id=13, officer=officer_5, allegation=allegation_3) OfficerAllegationFactory(id=14, officer=officer_4, allegation=allegation_4) OfficerAllegationFactory(id=15, officer=officer_5, allegation=allegation_4) expected_coaccused_data = [ { 'officer_id_1': 8563, 'officer_id_2': 8564, 'incident_date': '2007-12-31', 'accussed_count': 3 }, { 'officer_id_1': 8563, 'officer_id_2': 8565, 'incident_date': '2007-12-31', 'accussed_count': 3 }, { 'officer_id_1': 8563, 'officer_id_2': 8566, 'incident_date': '2007-12-31', 'accussed_count': 3 }, { 'officer_id_1': 8564, 'officer_id_2': 8565, 'incident_date': '2007-12-31', 'accussed_count': 3 }, { 'officer_id_1': 8564, 'officer_id_2': 8566, 'incident_date': '2007-12-31', 'accussed_count': 3 }, { 'officer_id_1': 8565, 'officer_id_2': 8566, 'incident_date': '2007-12-31', 'accussed_count': 3 }, ] expected_officers = [ { 'full_name': 'Edward May', 'id': 8563, 'percentile_allegation': '4.4000', 'percentile_allegation_civilian': '4.4000', 'percentile_allegation_internal': '5.5000', 'percentile_trr': '6.6000' }, { 'full_name': 'Jerome Finnigan', 'id': 8562, 'percentile_allegation': '1.1000', 'percentile_allegation_civilian': '1.1000', 'percentile_allegation_internal': '2.2000', 'percentile_trr': '3.3000' }, { 'full_name': 'Joe Parker', 'id': 8564, 'percentile_allegation': '7.7000', 'percentile_allegation_civilian': '7.7000', 'percentile_allegation_internal': '8.8000', 'percentile_trr': '9.9000' }, { 'full_name': 'John Sena', 'id': 8566, 'percentile_allegation': '13.1300', 'percentile_allegation_civilian': '13.1300', 'percentile_allegation_internal': '14.1400', 'percentile_trr': '15.1500' }, { 'full_name': 'John Snow', 'id': 8565, 'percentile_allegation': '10.1000', 'percentile_allegation_civilian': '10.1000', 'percentile_allegation_internal': '11.1100', 'percentile_trr': '12.1200' }, ] expected_list_event = ['2007-12-31'] expected_graph_data = { 'officers': expected_officers, 'coaccused_data': expected_coaccused_data, 'list_event': expected_list_event } officers = Officer.objects.filter( id__in=[officer.id for officer in [officer_1, officer_2, officer_3, officer_4, officer_5]] ) social_graph_data_query = SocialGraphDataQuery(officers, threshold=3, complaint_origin='OFFICER') expect(social_graph_data_query.graph_data()).to.eq(expected_graph_data) def test_graph_data_threshold_1_complaint_origin_is_all(self): officer_1 = OfficerFactory( id=8562, first_name='Jerome', last_name='Finnigan', complaint_percentile=1.1, civilian_allegation_percentile=1.1, internal_allegation_percentile=2.2, trr_percentile=3.3, ) officer_2 = OfficerFactory( id=8563, first_name='Edward', last_name='May', complaint_percentile=4.4, civilian_allegation_percentile=4.4, internal_allegation_percentile=5.5, trr_percentile=6.6, ) officer_3 = OfficerFactory( id=8564, first_name='Joe', last_name='Parker', complaint_percentile=7.7, civilian_allegation_percentile=7.7, internal_allegation_percentile=8.8, trr_percentile=9.9, ) allegation_1 = AllegationFactory( crid='123', is_officer_complaint=True, incident_date=datetime(2005, 12, 31, tzinfo=pytz.utc) ) allegation_2 = AllegationFactory( crid='456', is_officer_complaint=False, incident_date=datetime(2006, 12, 31, tzinfo=pytz.utc) ) allegation_3 = AllegationFactory( crid='789', is_officer_complaint=True, incident_date=datetime(2007, 12, 31, tzinfo=pytz.utc) ) OfficerAllegationFactory(id=1, officer=officer_1, allegation=allegation_1) OfficerAllegationFactory(id=2, officer=officer_2, allegation=allegation_1) OfficerAllegationFactory(id=3, officer=officer_1, allegation=allegation_2) OfficerAllegationFactory(id=4, officer=officer_2, allegation=allegation_2) OfficerAllegationFactory(id=5, officer=officer_1, allegation=allegation_3) OfficerAllegationFactory(id=6, officer=officer_2, allegation=allegation_3) OfficerAllegationFactory(id=7, officer=officer_3, allegation=allegation_3) expected_coaccused_data = [ { 'officer_id_1': 8562, 'officer_id_2': 8563, 'incident_date': '2005-12-31', 'accussed_count': 1 }, { 'officer_id_1': 8562, 'officer_id_2': 8563, 'incident_date': '2006-12-31', 'accussed_count': 2 }, { 'officer_id_1': 8562, 'officer_id_2': 8563, 'incident_date': '2007-12-31', 'accussed_count': 3 }, { 'officer_id_1': 8562, 'officer_id_2': 8564, 'incident_date': '2007-12-31', 'accussed_count': 1 }, { 'officer_id_1': 8563, 'officer_id_2': 8564, 'incident_date': '2007-12-31', 'accussed_count': 1 }, ] expected_officers = [ { 'full_name': 'Edward May', 'id': 8563, 'percentile_allegation': '4.4000', 'percentile_allegation_civilian': '4.4000', 'percentile_allegation_internal': '5.5000', 'percentile_trr': '6.6000' }, { 'full_name': 'Jerome Finnigan', 'id': 8562, 'percentile_allegation': '1.1000', 'percentile_allegation_civilian': '1.1000', 'percentile_allegation_internal': '2.2000', 'percentile_trr': '3.3000' }, { 'full_name': 'Joe Parker', 'id': 8564, 'percentile_allegation': '7.7000', 'percentile_allegation_civilian': '7.7000', 'percentile_allegation_internal': '8.8000', 'percentile_trr': '9.9000' }, ] expected_list_event = ['2005-12-31', '2006-12-31', '2007-12-31'] expected_graph_data = { 'officers': expected_officers, 'coaccused_data': expected_coaccused_data, 'list_event': expected_list_event } officers = Officer.objects.filter( id__in=[officer.id for officer in [officer_1, officer_2, officer_3]] ) social_graph_data_query = SocialGraphDataQuery( officers, threshold=1, complaint_origin='ALL' ) expect(social_graph_data_query.graph_data()).to.eq(expected_graph_data) def test_graph_data_threshold_3_complaint_origin_is_all(self): officer_1 = OfficerFactory( id=8562, first_name='Jerome', last_name='Finnigan', complaint_percentile=1.1, civilian_allegation_percentile=1.1, internal_allegation_percentile=2.2, trr_percentile=3.3, ) officer_2 = OfficerFactory( id=8563, first_name='Edward', last_name='May', complaint_percentile=4.4, civilian_allegation_percentile=4.4, internal_allegation_percentile=5.5, trr_percentile=6.6, ) officer_3 = OfficerFactory( id=8564, first_name='Joe', last_name='Parker', complaint_percentile=7.7, civilian_allegation_percentile=7.7, internal_allegation_percentile=8.8, trr_percentile=9.9, ) officer_4 = OfficerFactory( id=8565, first_name='John', last_name='Snow', complaint_percentile=10.10, civilian_allegation_percentile=10.10, internal_allegation_percentile=11.11, trr_percentile=12.12, ) officer_5 = OfficerFactory( id=8566, first_name='John', last_name='Sena', complaint_percentile=13.13, civilian_allegation_percentile=13.13, internal_allegation_percentile=14.14, trr_percentile=15.15, ) allegation_1 = AllegationFactory( crid='123', is_officer_complaint=False, incident_date=datetime(2005, 12, 31, tzinfo=pytz.utc) ) allegation_2 = AllegationFactory( crid='456', is_officer_complaint=True, incident_date=datetime(2006, 12, 31, tzinfo=pytz.utc) ) allegation_3 = AllegationFactory( crid='789', is_officer_complaint=True, incident_date=datetime(2007, 12, 31, tzinfo=pytz.utc) ) allegation_4 = AllegationFactory( crid='987', is_officer_complaint=False, incident_date=datetime(2008, 12, 31, tzinfo=pytz.utc) ) OfficerAllegationFactory(id=1, officer=officer_1, allegation=allegation_1) OfficerAllegationFactory(id=2, officer=officer_2, allegation=allegation_1) OfficerAllegationFactory(id=3, officer=officer_2, allegation=allegation_2) OfficerAllegationFactory(id=4, officer=officer_3, allegation=allegation_2) OfficerAllegationFactory(id=5, officer=officer_2, allegation=allegation_3) OfficerAllegationFactory(id=6, officer=officer_3, allegation=allegation_3) OfficerAllegationFactory(id=7, officer=officer_3, allegation=allegation_1) OfficerAllegationFactory(id=8, officer=officer_4, allegation=allegation_1) OfficerAllegationFactory(id=9, officer=officer_4, allegation=allegation_2) OfficerAllegationFactory(id=10, officer=officer_4, allegation=allegation_3) OfficerAllegationFactory(id=11, officer=officer_5, allegation=allegation_1) OfficerAllegationFactory(id=12, officer=officer_5, allegation=allegation_2) OfficerAllegationFactory(id=13, officer=officer_5, allegation=allegation_3) OfficerAllegationFactory(id=14, officer=officer_4, allegation=allegation_4) OfficerAllegationFactory(id=15, officer=officer_5, allegation=allegation_4) expected_coaccused_data = [ { 'officer_id_1': 8563, 'officer_id_2': 8564, 'incident_date': '2007-12-31', 'accussed_count': 3 }, { 'officer_id_1': 8563, 'officer_id_2': 8565, 'incident_date': '2007-12-31', 'accussed_count': 3 }, { 'officer_id_1': 8563, 'officer_id_2': 8566, 'incident_date': '2007-12-31', 'accussed_count': 3 }, { 'officer_id_1': 8564, 'officer_id_2': 8565, 'incident_date': '2007-12-31', 'accussed_count': 3 }, { 'officer_id_1': 8564, 'officer_id_2': 8566, 'incident_date': '2007-12-31', 'accussed_count': 3 }, { 'officer_id_1': 8565, 'officer_id_2': 8566, 'incident_date': '2007-12-31', 'accussed_count': 3 }, { 'officer_id_1': 8565, 'officer_id_2': 8566, 'incident_date': '2008-12-31', 'accussed_count': 4 }, ] expected_officers = [ { 'full_name': 'Edward May', 'id': 8563, 'percentile_allegation': '4.4000', 'percentile_allegation_civilian': '4.4000', 'percentile_allegation_internal': '5.5000', 'percentile_trr': '6.6000' }, { 'full_name': 'Jerome Finnigan', 'id': 8562, 'percentile_allegation': '1.1000', 'percentile_allegation_civilian': '1.1000', 'percentile_allegation_internal': '2.2000', 'percentile_trr': '3.3000' }, { 'full_name': 'Joe Parker', 'id': 8564, 'percentile_allegation': '7.7000', 'percentile_allegation_civilian': '7.7000', 'percentile_allegation_internal': '8.8000', 'percentile_trr': '9.9000' }, { 'full_name': 'John Sena', 'id': 8566, 'percentile_allegation': '13.1300', 'percentile_allegation_civilian': '13.1300', 'percentile_allegation_internal': '14.1400', 'percentile_trr': '15.1500' }, { 'full_name': 'John Snow', 'id': 8565, 'percentile_allegation': '10.1000', 'percentile_allegation_civilian': '10.1000', 'percentile_allegation_internal': '11.1100', 'percentile_trr': '12.1200' }, ] expected_list_event = ['2007-12-31', '2008-12-31'] expected_graph_data = { 'officers': expected_officers, 'coaccused_data': expected_coaccused_data, 'list_event': expected_list_event } officers = Officer.objects.filter( id__in=[officer.id for officer in [officer_1, officer_2, officer_3, officer_4, officer_5]] ) social_graph_data_query = SocialGraphDataQuery( officers, threshold=3, complaint_origin='ALL' ) expect(social_graph_data_query.graph_data()).to.eq(expected_graph_data) def test_show_connected_officers(self): officer_1 = OfficerFactory( id=8000, first_name='Jerome', last_name='Finnigan', complaint_percentile=1.1, civilian_allegation_percentile=1.1, internal_allegation_percentile=2.2, trr_percentile=3.3, ) officer_2 = OfficerFactory( id=8001, first_name='Edward', last_name='May', complaint_percentile=4.4, civilian_allegation_percentile=4.4, internal_allegation_percentile=5.5, trr_percentile=6.6, ) officer_3 = OfficerFactory( id=8002, first_name='Joe', last_name='Parker', complaint_percentile=7.7, civilian_allegation_percentile=7.7, internal_allegation_percentile=8.8, trr_percentile=9.9, ) officer_4 = OfficerFactory( id=8003, first_name='John', last_name='Snow', complaint_percentile=10.10, civilian_allegation_percentile=10.10, internal_allegation_percentile=11.11, trr_percentile=12.12, ) officer_5 = OfficerFactory( id=8004, first_name='John', last_name='Sena', complaint_percentile=13.13, civilian_allegation_percentile=13.13, internal_allegation_percentile=14.14, trr_percentile=15.15, ) officer_6 = OfficerFactory( id=8005, first_name='Tom', last_name='Cruise', complaint_percentile=16.16, civilian_allegation_percentile=16.16, internal_allegation_percentile=17.17, trr_percentile=18.18, ) officer_7 = OfficerFactory( id=8006, first_name='Robert', last_name='Long', complaint_percentile=19.19, civilian_allegation_percentile=19.19, internal_allegation_percentile=20.20, trr_percentile=21.21, ) allegation_1 = AllegationFactory( crid='123', is_officer_complaint=False, incident_date=datetime(2005, 12, 31, tzinfo=pytz.utc) ) allegation_2 = AllegationFactory( crid='456', is_officer_complaint=True, incident_date=datetime(2006, 12, 31, tzinfo=pytz.utc) ) allegation_3 = AllegationFactory( crid='789', is_officer_complaint=True, incident_date=datetime(2007, 12, 31, tzinfo=pytz.utc) ) allegation_4 = AllegationFactory( crid='987', is_officer_complaint=False, incident_date=datetime(2008, 12, 31, tzinfo=pytz.utc) ) allegation_5 = AllegationFactory( crid='555', is_officer_complaint=False, incident_date=datetime(2009, 12, 31, tzinfo=pytz.utc) ) allegation_6 = AllegationFactory( crid='666', is_officer_complaint=False, incident_date=datetime(2010, 12, 31, tzinfo=pytz.utc) ) allegation_7 = AllegationFactory( crid='777', is_officer_complaint=False, incident_date=datetime(2011, 12, 31, tzinfo=pytz.utc) ) allegation_8 = AllegationFactory( crid='888', is_officer_complaint=False, incident_date=datetime(2012, 12, 31, tzinfo=pytz.utc) ) allegation_9 = AllegationFactory( crid='999', is_officer_complaint=False, incident_date=datetime(2013, 12, 31, tzinfo=pytz.utc) ) allegation_10 = AllegationFactory( crid='1000', is_officer_complaint=False, incident_date=datetime(2014, 12, 31, tzinfo=pytz.utc) ) OfficerAllegationFactory(id=1, officer=officer_1, allegation=allegation_1) OfficerAllegationFactory(id=2, officer=officer_2, allegation=allegation_1) OfficerAllegationFactory(id=3, officer=officer_2, allegation=allegation_2) OfficerAllegationFactory(id=4, officer=officer_3, allegation=allegation_2) OfficerAllegationFactory(id=5, officer=officer_2, allegation=allegation_3) OfficerAllegationFactory(id=6, officer=officer_3, allegation=allegation_3) OfficerAllegationFactory(id=7, officer=officer_2, allegation=allegation_4) OfficerAllegationFactory(id=8, officer=officer_4, allegation=allegation_4) OfficerAllegationFactory(id=9, officer=officer_2, allegation=allegation_5) OfficerAllegationFactory(id=10, officer=officer_4, allegation=allegation_5) OfficerAllegationFactory(id=11, officer=officer_3, allegation=allegation_6) OfficerAllegationFactory(id=12, officer=officer_5, allegation=allegation_6) OfficerAllegationFactory(id=13, officer=officer_3, allegation=allegation_7) OfficerAllegationFactory(id=14, officer=officer_5, allegation=allegation_7) OfficerAllegationFactory(id=15, officer=officer_3, allegation=allegation_8) OfficerAllegationFactory(id=16, officer=officer_6, allegation=allegation_8) OfficerAllegationFactory(id=17, officer=officer_3, allegation=allegation_9) OfficerAllegationFactory(id=18, officer=officer_6, allegation=allegation_9) OfficerAllegationFactory(id=19, officer=officer_3, allegation=allegation_10) OfficerAllegationFactory(id=20, officer=officer_7, allegation=allegation_10) expected_graph_data = { 'officers': [ { 'full_name': 'Edward May', 'id': 8001, 'percentile_allegation': '4.4000', 'percentile_allegation_civilian': '4.4000', 'percentile_allegation_internal': '5.5000', 'percentile_trr': '6.6000' }, { 'full_name': 'Jerome Finnigan', 'id': 8000, 'percentile_allegation': '1.1000', 'percentile_allegation_civilian': '1.1000', 'percentile_allegation_internal': '2.2000', 'percentile_trr': '3.3000' }, { 'full_name': 'Joe Parker', 'id': 8002, 'percentile_allegation': '7.7000', 'percentile_allegation_civilian': '7.7000', 'percentile_allegation_internal': '8.8000', 'percentile_trr': '9.9000' }, { 'full_name': 'John Sena', 'id': 8004, 'percentile_allegation': '13.1300', 'percentile_allegation_civilian': '13.1300', 'percentile_allegation_internal': '14.1400', 'percentile_trr': '15.1500' }, { 'full_name': 'John Snow', 'id': 8003, 'percentile_allegation': '10.1000', 'percentile_allegation_civilian': '10.1000', 'percentile_allegation_internal': '11.1100', 'percentile_trr': '12.1200' }, { 'full_name': 'Tom Cruise', 'id': 8005, 'percentile_allegation': '16.1600', 'percentile_allegation_civilian': '16.1600', 'percentile_allegation_internal': '17.1700', 'percentile_trr': '18.1800' }, ], 'coaccused_data': [ { 'officer_id_1': 8001, 'officer_id_2': 8002, 'incident_date': '2007-12-31', 'accussed_count': 2 }, { 'officer_id_1': 8001, 'officer_id_2': 8003, 'incident_date': '2009-12-31', 'accussed_count': 2 }, { 'officer_id_1': 8002, 'officer_id_2': 8004, 'incident_date': '2011-12-31', 'accussed_count': 2 }, { 'officer_id_1': 8002, 'officer_id_2': 8005, 'incident_date': '2013-12-31', 'accussed_count': 2 } ], 'list_event': [ '2007-12-31', '2009-12-31', '2011-12-31', '2013-12-31', ] } officers = Officer.objects.filter( id__in=[officer.id for officer in [officer_1, officer_2, officer_3]] ) social_graph_data_query = SocialGraphDataQuery( officers, threshold=2, complaint_origin='ALL', show_connected_officers=True ) expect(social_graph_data_query.graph_data()).to.eq(expected_graph_data) def test_graph_data_empty_officers(self): social_graph_data_query = SocialGraphDataQuery(Officer.objects.none(), threshold=2, complaint_origin='ALL') expect(social_graph_data_query.graph_data()).to.be.empty() def test_all_officers_default(self): officer_1 = OfficerFactory( id=8562, first_name='Jerome', last_name='Finnigan', civilian_allegation_percentile='88.8800', internal_allegation_percentile='77.7700', trr_percentile='66.6600', ) officer_2 = OfficerFactory( id=8563, first_name='Edward', last_name='May', civilian_allegation_percentile='55.6600', internal_allegation_percentile='66.7700', trr_percentile='77.8800', ) officer_3 = OfficerFactory( id=8564, first_name='Joe', last_name='Parker', civilian_allegation_percentile='44.4400', internal_allegation_percentile='33.3300', trr_percentile='22.2200', ) officers = Officer.objects.filter( id__in=[officer.id for officer in [officer_1, officer_2, officer_3]] ) social_graph_data_query = SocialGraphDataQuery(officers) expect(list(social_graph_data_query.all_officers())).to.eq([officer_2, officer_1, officer_3]) def test_all_officers_with_show_connected_officers(self): officer_1 = OfficerFactory(id=8000, first_name='Jerome', last_name='Finnigan') officer_2 = OfficerFactory(id=8001, first_name='Edward', last_name='May') officer_3 = OfficerFactory(id=8002, first_name='Joe', last_name='Parker') officer_4 = OfficerFactory(id=8003, first_name='John', last_name='Snow') officer_5 = OfficerFactory(id=8004, first_name='John', last_name='Sena') officer_6 = OfficerFactory(id=8005, first_name='Tom', last_name='Cruise') officer_7 = OfficerFactory(id=8006, first_name='Robert', last_name='Long') allegation_1 = AllegationFactory( crid='123', is_officer_complaint=False, incident_date=datetime(2005, 12, 31, tzinfo=pytz.utc) ) allegation_2 = AllegationFactory( crid='456', is_officer_complaint=True, incident_date=datetime(2006, 12, 31, tzinfo=pytz.utc) ) allegation_3 = AllegationFactory( crid='789', is_officer_complaint=True, incident_date=datetime(2007, 12, 31, tzinfo=pytz.utc) ) allegation_4 = AllegationFactory( crid='987', is_officer_complaint=False, incident_date=datetime(2008, 12, 31, tzinfo=pytz.utc) ) allegation_5 = AllegationFactory( crid='555', is_officer_complaint=False, incident_date=datetime(2009, 12, 31, tzinfo=pytz.utc) ) allegation_6 = AllegationFactory( crid='666', is_officer_complaint=False, incident_date=datetime(2010, 12, 31, tzinfo=pytz.utc) ) allegation_7 = AllegationFactory( crid='777', is_officer_complaint=False, incident_date=datetime(2011, 12, 31, tzinfo=pytz.utc) ) allegation_8 = AllegationFactory( crid='888', is_officer_complaint=False, incident_date=datetime(2012, 12, 31, tzinfo=pytz.utc) ) allegation_9 = AllegationFactory( crid='999', is_officer_complaint=False, incident_date=datetime(2013, 12, 31, tzinfo=pytz.utc) ) allegation_10 = AllegationFactory( crid='1000', is_officer_complaint=False, incident_date=datetime(2014, 12, 31, tzinfo=pytz.utc) ) OfficerAllegationFactory(id=1, officer=officer_1, allegation=allegation_1) OfficerAllegationFactory(id=2, officer=officer_2, allegation=allegation_1) OfficerAllegationFactory(id=3, officer=officer_2, allegation=allegation_2) OfficerAllegationFactory(id=4, officer=officer_3, allegation=allegation_2) OfficerAllegationFactory(id=5, officer=officer_2, allegation=allegation_3) OfficerAllegationFactory(id=6, officer=officer_3, allegation=allegation_3) OfficerAllegationFactory(id=7, officer=officer_2, allegation=allegation_4) OfficerAllegationFactory(id=8, officer=officer_4, allegation=allegation_4) OfficerAllegationFactory(id=9, officer=officer_2, allegation=allegation_5) OfficerAllegationFactory(id=10, officer=officer_4, allegation=allegation_5) OfficerAllegationFactory(id=11, officer=officer_3, allegation=allegation_6) OfficerAllegationFactory(id=12, officer=officer_5, allegation=allegation_6) OfficerAllegationFactory(id=13, officer=officer_3, allegation=allegation_7) OfficerAllegationFactory(id=14, officer=officer_5, allegation=allegation_7) OfficerAllegationFactory(id=15, officer=officer_3, allegation=allegation_8) OfficerAllegationFactory(id=16, officer=officer_6, allegation=allegation_8) OfficerAllegationFactory(id=17, officer=officer_3, allegation=allegation_9) OfficerAllegationFactory(id=18, officer=officer_6, allegation=allegation_9) OfficerAllegationFactory(id=19, officer=officer_3, allegation=allegation_10) OfficerAllegationFactory(id=20, officer=officer_7, allegation=allegation_10) officers = Officer.objects.filter( id__in=[officer.id for officer in [officer_1, officer_2, officer_3, officer_4, officer_5, officer_6]] ) social_graph_data_query = SocialGraphDataQuery( officers, threshold=2, complaint_origin='ALL', show_connected_officers=True ) expected_officers = [officer_2, officer_1, officer_3, officer_5, officer_4, officer_6] expect(list(social_graph_data_query.all_officers())).to.eq(expected_officers) def test_allegations_default(self): officer_1 = OfficerFactory(id=8562, first_name='Jerome', last_name='Finnigan') officer_2 = OfficerFactory(id=8563, first_name='Edward', last_name='May') officer_3 = OfficerFactory(id=8564, first_name='Joe', last_name='Parker') officer_4 = OfficerFactory(id=8565, first_name='Jon', last_name='Snow') allegation_1 = AllegationFactory( crid='123', is_officer_complaint=False, incident_date=datetime(2005, 12, 31, tzinfo=pytz.utc), ) allegation_2 = AllegationFactory( crid='456', is_officer_complaint=False, incident_date=datetime(2006, 12, 31, tzinfo=pytz.utc), ) allegation_3 = AllegationFactory( crid='789', is_officer_complaint=False, incident_date=datetime(2007, 12, 31, tzinfo=pytz.utc), ) allegation_4 = AllegationFactory( crid='987', is_officer_complaint=False, incident_date=datetime(2008, 12, 31, tzinfo=pytz.utc), ) OfficerAllegationFactory(id=1, officer=officer_1, allegation=allegation_1) OfficerAllegationFactory(id=2, officer=officer_2, allegation=allegation_1) OfficerAllegationFactory(id=3, officer=officer_3, allegation=allegation_1) OfficerAllegationFactory(id=4, officer=officer_1, allegation=allegation_2) OfficerAllegationFactory(id=5, officer=officer_2, allegation=allegation_2) OfficerAllegationFactory(id=6, officer=officer_3, allegation=allegation_2) OfficerAllegationFactory(id=7, officer=officer_1, allegation=allegation_3) OfficerAllegationFactory(id=8, officer=officer_2, allegation=allegation_3) OfficerAllegationFactory(id=9, officer=officer_3, allegation=allegation_4) OfficerAllegationFactory(id=10, officer=officer_4, allegation=allegation_4) officers = Officer.objects.filter( id__in=[officer.id for officer in [officer_1, officer_2, officer_3, officer_4]] ) social_graph_data_query = SocialGraphDataQuery(officers) expect(list(social_graph_data_query.allegations())).to.eq([allegation_1, allegation_2, allegation_3]) def test_empty_allegations(self): officer_1 = OfficerFactory(id=8562, first_name='Jerome', last_name='Finnigan') officer_2 = OfficerFactory(id=8563, first_name='Edward', last_name='May') officers = Officer.objects.filter( id__in=[officer.id for officer in [officer_1, officer_2]] ) social_graph_data_query = SocialGraphDataQuery(officers) expect(social_graph_data_query.allegations()).to.be.empty() def test_graph_data_without_officers(self): social_graph_data_query = SocialGraphDataQuery(None) expect(social_graph_data_query.coaccused_data).to.eq([]) social_graph_data_query = SocialGraphDataQuery(Officer.objects.none()) expect(social_graph_data_query.coaccused_data).to.eq([]) def test_allegation_without_officers(self): social_graph_data_query = SocialGraphDataQuery(None) expect(social_graph_data_query.allegation_ids).to.eq([]) social_graph_data_query = SocialGraphDataQuery(Officer.objects.none()) expect(social_graph_data_query.allegation_ids).to.eq([])

38.285621

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0.102698

0.027522

0.021406

0.958685

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0.089542

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58,577

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0.721948

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false

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7

7b9a01a080996a2efc7a0b7c2db4ea02c3731ccd

16,587

py

Python

eval.py

arka816/php-node-transpiler

60228d45d546523b2bcaec6a9b667182ed691817

[ "MIT" ]

null

eval.py

arka816/php-node-transpiler

60228d45d546523b2bcaec6a9b667182ed691817

[ "MIT" ]

null

eval.py

arka816/php-node-transpiler

60228d45d546523b2bcaec6a9b667182ed691817

[ "MIT" ]

null

# ARITHMETIC STRING EVALUATION PROGRAM # AUTHOR ARKA import sys import math stack=[] degflag = True def factorial(n): n=int(n) if n==1 or n==0: return 1 fact = 1 for i in range(1, n+1): fact = fact*i return fact def evalRec(string): global stack, degflag if 'sin' in string: while string.find('sin') != -1: l=len(string) index = string.find("sin") if string[index+3] == "(": stack.append("(") i=index + 3 while len(stack) > 0 and i < l - 1: i += 1 if string[i] == "(": stack.append("(") elif string[i] == ")": try: stack.pop() except: print("invalid bracket structure") sys.exit() end = i argument = string[index+3: end+1] else: print("no brackets after sin call") sys.exit() angle=float(eval(argument)) if degflag: angle = float(angle * math.pi / 180) string = string[0:index] + str(math.sin(angle)) + string[end+1: len(string)] return eval(string) elif 'cos' in string: while string.find('cos') != -1: l=len(string) index = string.find("cos") if string[index+3] == "(": stack.append("(") i=index + 3 while len(stack) > 0 and i < l - 1: i += 1 if string[i] == "(": stack.append("(") elif string[i] == ")": try: stack.pop() except: print("invalid bracket structure") sys.exit() end = i argument = string[index+3: end+1] else: print("no brackets after cos call") sys.exit() angle=float(eval(argument)) if degflag: angle = float(angle * math.pi / 180) string = string[0:index] + str(math.cos(angle)) + string[end+1: len(string)] return eval(string) elif 'tan' in string: while string.find('tan') != -1: l=len(string) index = string.find("tan") if string[index+3] == "(": stack.append("(") i=index + 3 while len(stack) > 0 and i < l - 1: i += 1 if string[i] == "(": stack.append("(") elif string[i] == ")": try: stack.pop() except: print("invalid bracket structure") sys.exit() end = i argument = string[index+3: end+1] else: print("no brackets after tan call") sys.exit() angle=float(eval(argument)) if degflag: angle = float(angle * math.pi / 180) string = string[0:index] + str(math.tan(angle)) + string[end+1: len(string)] return eval(string) elif 'ln' in string: while string.find('ln') != -1: l=len(string) index = string.find("ln") if string[index+2] == "(": stack.append("(") i=index + 2 while len(stack) > 0 and i < l - 1: i += 1 if string[i] == "(": stack.append("(") elif string[i] == ")": try: stack.pop() except: print("invalid bracket structure") sys.exit() end = i argument = string[index+2: end+1] else: print("no brackets after ln call") sys.exit() string = string[0:index] + str(float(math.log(eval(argument)))) + string[end+1: len(string)] return eval(string) elif 'log' in string: while string.find('log') != -1: l=len(string) index = string.find("log") if string[index+3] == "(": stack.append("(") i=index + 3 while len(stack) > 0 and i < l - 1: i += 1 if string[i] == "(": stack.append("(") elif string[i] == ")": try: stack.pop() except: print("invalid bracket structure") sys.exit() end = i argument = string[index+3: end+1] else: print("no brackets after log call") sys.exit() string = string[0:index] + str(float(math.log(eval(argument), 10))) + string[end+1: len(string)] return eval(string) elif "!" in string: while string.find('!') != -1: l=len(string) index = string.find("!") if string[index-1] == ")": stack.append(")") i=index - 1 while len(stack) > 0 and i > 0: i -= 1 if string[i] == ")": stack.append(")") elif string[i] == "(": try: stack.pop() except: print("invalid bracket structure") sys.exit() start = i number = string[start:index] else: i = index - 1 while i >= 0 and ((string[i] >= '0' and string[i] <= '9') or string[i] == "."): i-=1 start=i+1 number = string[start:index] string = string[0:start] + str(int(factorial(eval(number)))) + string[index+1: len(string)] return eval(string) elif "^" in string: while string.find('^') != -1: l=len(string) index = string.find("^") if string[index-1] == ")": stack.append(")") i=index - 1 while len(stack) > 0 and i > 0: i -= 1 if string[i] == ")": stack.append(")") elif string[i] == "(": try: stack.pop() except: print("invalid bracket structure") sys.exit() start = i base = string[start:index] else: i = index - 1 while i >= 0 and ((string[i] >= '0' and string[i] <= '9') or string[i] == "."): i-=1 start=i+1 base = string[start:index] if string[index+1] == "(": stack.append("(") i=index + 1 while len(stack) > 0 and i < l - 1: i += 1 if string[i] == "(": stack.append("(") elif string[i] == ")": try: stack.pop() except: print("invalid bracket structure") sys.exit() end = i exponent = string[index+1: end+1] else: i=index+1 while i < l and ((string[i] >= '0' and string[i] <= '9') or string[i] == "."): i+=1 end = i-1 exponent = string[index+1: end+1] string = string[0:start] + str(float(eval(base) ** eval(exponent))) + string[end+1: len(string)] return eval(string) elif "/" in string: while string.find('/') != -1: l=len(string) index = string.find("/") if string[index-1] == ")": stack.append(")") i=index - 1 while len(stack) > 0 and i > 0: i -= 1 if string[i] == ")": stack.append(")") elif string[i] == "(": try: stack.pop() except: print("invalid bracket structure") sys.exit() start = i dividend = string[start:index] else: i = index - 1 while i >= 0 and ((string[i] >= '0' and string[i] <= '9') or string[i] == "."): i-=1 start=i+1 dividend = string[start:index] if string[index+1] == "(": stack.append("(") i=index + 1 while len(stack) > 0 and i < l - 1: i += 1 if string[i] == "(": stack.append("(") elif string[i] == ")": try: stack.pop() except: print("invalid bracket structure") sys.exit() end = i divisor = string[index+1: end+1] else: i=index+1 while i < l and ((string[i] >= '0' and string[i] <= '9') or string[i] == "."): i+=1 end = i-1 divisor = string[index+1: end+1] string = string[0:start] + str(format(float(eval(dividend) / eval(divisor)), '.6f')) + string[end+1: len(string)] return eval(string) elif "*" in string: while string.find('*') != -1: l=len(string) index = string.find("*") if string[index-1] == ")": stack.append(")") i=index - 1 while len(stack) > 0 and i > 0: i -= 1 if string[i] == ")": stack.append(")") elif string[i] == "(": try: stack.pop() except: print("invalid bracket structure") sys.exit() start = i multiplicand = string[start:index] else: i = index - 1 while i >= 0 and ((string[i] >= '0' and string[i] <= '9') or string[i] == "."): i-=1 start=i+1 multiplicand = string[start:index] if string[index+1] == "(": stack.append("(") i=index+1 while len(stack) > 0 and i < l - 1: i += 1 if string[i] == "(": stack.append("(") elif string[i] == ")": try: stack.pop() except: print("invalid bracket structure") sys.exit() end = i multiplier = string[index+1: end+1] else: i=index+1 while i < l and ((string[i] >= '0' and string[i] <= '9') or string[i] == "."): i+=1 end = i-1 multiplier = string[index+1: end+1] string = string[0:start] + str(float(eval(multiplicand) * eval(multiplier))) + string[end+1: len(string)] return eval(string) elif "+" in string: while string.find('+') != -1: l=len(string) index = string.find("+") if string[index-1] == ")": stack.append(")") i=index-1 while len(stack) > 0 and i > 0: i -= 1 if string[i] == ")": stack.append(")") elif string[i] == "(": try: stack.pop() except: print("invalid bracket structure") sys.exit() start = i addend = string[start:index] else: i = index - 1 while i >= 0 and ((string[i] >= '0' and string[i] <= '9') or string[i] == "."): i-=1 start=i+1 addend = string[start:index] if string[index+1] == "(": stack.append("(") i=index+1 while len(stack) > 0 and i < l - 1: i += 1 if string[i] == "(": stack.append("(") elif string[i] == ")": try: stack.pop() except: print("invalid bracket structure") sys.exit() end = i adder = string[index+1: end+1] else: i=index+1 while i < l and ((string[i] >= '0' and string[i] <= '9') or string[i] == "."): i+=1 end = i-1 adder = string[index+1: end+1] string = string[0:start] + str(float(eval(addend) + eval(adder))) + string[end+1: len(string)] return eval(string) elif "-" in string: while string.find('-') != -1: l=len(string) index = string.find("-") if string[index-1] == ")": stack.append(")") i=index-1 while len(stack) > 0 and i > 0: i -= 1 if string[i] == ")": stack.append(")") elif string[i] == "(": try: stack.pop() except: print("invalid bracket structure") sys.exit() start = i minuend = string[start:index] else: i = index - 1 while i >= 0 and ((string[i] >= '0' and string[i] <= '9') or string[i] == "."): i-=1 start=i+1 minuend = string[start:index] if string[index+1] == "(": stack.append("(") i=index+1 while len(stack) > 0 and i < l - 1: i += 1 if string[i] == "(": stack.append("(") elif string[i] == ")": try: stack.pop() except: print("invalid bracket structure") sys.exit() end = i subtrahend = string[index+1: end+1] else: i=index+1 while i < l and ((string[i] >= '0' and string[i] <= '9') or string[i] == "."): i+=1 end = i-1 subtrahend = string[index+1: end+1] string = string[0:start] + str(float(eval(minuend) - eval(subtrahend))) + string[end+1: len(string)] return eval(string) else: string = string.strip("(").strip(")") f=float(string) return f def evalStr(string): string=string.replace(" ", "") return evalRec(string)

38.845433

126

0.341412

1,508

16,587

3.755305

0.055703

0.080346

0.046618

0.888222

0.864206

0.850079

0.822179

0.815999

0.809112

0

0.02866

0.533008

16,587

427

127

38.845433

0.702427

0.002894

0

0.827338

0

0.043945

0

1

0.007194

false

0

0.004796

0

0.047962

0.05036

0

null

0

1

0

1

0

1

0

null

0

8

7baea41aba860080e3af392b8f071e1e62b95a08

180

py

Python

travello/urls.py

anjali-patel21/Travelling-website-Django

ecd25d86b5a973b6f7114ecb557647e26c027bf9

[ "MIT" ]

null

travello/urls.py

anjali-patel21/Travelling-website-Django

ecd25d86b5a973b6f7114ecb557647e26c027bf9

[ "MIT" ]

null

travello/urls.py

anjali-patel21/Travelling-website-Django

ecd25d86b5a973b6f7114ecb557647e26c027bf9

[ "MIT" ]

null

from django.urls import include, path from django.urls import path from django.contrib import admin from . import views urlpatterns = [ path('',views.index, name = 'index') ]

20

40

0.733333

25

180

5.28

0.48

0.227273

0.212121

0.30303

0

0.166667

180

9

41

20

0.88

0

0.027624

0

1

0

false

0

0.571429

0

0.571429

0

1

0

null

1

0

1

0

null

0

1

0

1

0

7

c874f51ef66ae48375cffeafbd391146b1173c3b

2,294

py

Python

tests/test_urls.py

anoroozian/pyvt

bf36f833f1f1b7d93169fd9ad451e06b7d46afc1

[ "MIT" ]

null

tests/test_urls.py

anoroozian/pyvt

bf36f833f1f1b7d93169fd9ad451e06b7d46afc1

[ "MIT" ]

null

tests/test_urls.py

anoroozian/pyvt

bf36f833f1f1b7d93169fd9ad451e06b7d46afc1

[ "MIT" ]

null

# Copyright (c) 2009-2014 Arman Noroozian from unittest import TestCase import json import pyvt class QueryURLS(TestCase): def setUp(self): self.api = pyvt.API('~/.virustotal.key') def test_retriece_single_url(self): self.api._urls_per_retrieve = 4 response = self.api.retrieve('http://3dtaller.com.ar/') print(json.dumps(response, indent=2)) def test_retrieve_multiple_urls_within_limit(self): self.api._urls_per_retrieve = 4 response = self.api.retrieve(['http://3dtaller.com.ar/', 'http://3dtaller.com.ar/wp-content/themes/theme1392/js/jquery.loader.js', 'http://3dtaller.com.ar/wp-includes/js/swfobject.js', 'http://3dtaller.com.ar/wp-content/themes/theme1392/js/modernizr-2.0.js']) print(json.dumps(response, indent=2)) def test_retrieve_multiple_urls_exceed_limit_1(self): self.api._urls_per_retrieve = 1 response = self.api.retrieve(['http://3dtaller.com.ar/', 'http://3dtaller.com.ar/wp-content/themes/theme1392/js/jquery.loader.js', 'http://3dtaller.com.ar/wp-includes/js/swfobject.js', 'http://3dtaller.com.ar/wp-content/themes/theme1392/js/modernizr-2.0.js', 'http://3dtaller.com.ar/wp-content/themes/theme1392/js/custom.js']) print(json.dumps(response, indent=2)) def test_retrieve_multiple_urls_exceed_limit_2(self): self.api._urls_per_retrieve = 2 response = self.api.retrieve(['http://3dtaller.com.ar/', 'http://3dtaller.com.ar/wp-content/themes/theme1392/js/jquery.loader.js', 'http://3dtaller.com.ar/wp-includes/js/swfobject.js', 'http://3dtaller.com.ar/wp-content/themes/theme1392/js/modernizr-2.0.js', 'http://3dtaller.com.ar/wp-content/themes/theme1392/js/custom.js', 'http://3dtaller.com.ar/wp-content/themes/theme1392/js/jquery-1.6.4.min.js']) print(json.dumps(response, indent=2))

49.869565

115

0.572363

277

2,294

4.624549

0.202166

0.149883

0.187354

0.212334

0.856362

0.815769

0.791569

0

0.048437

0.289015

2,294

45

116

50.977778

0.736971

0.017001

0

0.5

0

0.264706

0.390222

0

1

0.147059

false

0

0.088235

0

0.264706

0.117647

0

null

0

1

0

1

0

null

0

9

cdb1f1dee7decc2b10e56adb08d8b2e928026ff3

2,119

py

Python

urbarium/character/migrations/0003_auto_20200513_1832.py

nikerzetic/zacasno-ime

7ca42665a0f64cae7233c994c879f2d81502efec

[ "MIT" ]

null

urbarium/character/migrations/0003_auto_20200513_1832.py

nikerzetic/zacasno-ime

7ca42665a0f64cae7233c994c879f2d81502efec

[ "MIT" ]

5

2021-03-30T14:18:31.000Z

2021-09-22T19:35:18.000Z

urbarium/character/migrations/0003_auto_20200513_1832.py

nikerzetic/zacasno-ime

7ca42665a0f64cae7233c994c879f2d81502efec

[ "MIT" ]

1

2020-09-08T10:38:54.000Z

# Generated by Django 3.0.4 on 2020-05-13 16:32 import django.core.validators from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('character', '0002_character_public'), ] operations = [ migrations.RemoveField( model_name='character', name='high_ability', ), migrations.RemoveField( model_name='character', name='low_ability', ), migrations.AddField( model_name='character', name='charisma', field=models.IntegerField(blank=True, null=True, validators=[django.core.validators.MinValueValidator(1), django.core.validators.MaxValueValidator(30)]), ), migrations.AddField( model_name='character', name='constitution', field=models.IntegerField(blank=True, null=True, validators=[django.core.validators.MinValueValidator(1), django.core.validators.MaxValueValidator(30)]), ), migrations.AddField( model_name='character', name='dexterity', field=models.IntegerField(blank=True, null=True, validators=[django.core.validators.MinValueValidator(1), django.core.validators.MaxValueValidator(30)]), ), migrations.AddField( model_name='character', name='intelligence', field=models.IntegerField(blank=True, null=True, validators=[django.core.validators.MinValueValidator(1), django.core.validators.MaxValueValidator(30)]), ), migrations.AddField( model_name='character', name='strength', field=models.IntegerField(blank=True, null=True, validators=[django.core.validators.MinValueValidator(1), django.core.validators.MaxValueValidator(30)]), ), migrations.AddField( model_name='character', name='wisdom', field=models.IntegerField(blank=True, null=True, validators=[django.core.validators.MinValueValidator(1), django.core.validators.MaxValueValidator(30)]), ), ]

39.981132

165

0.638509

198

2,119

6.772727

0.242424

0.096943

0.193885

0.131245

0.811335

0.717375

0

0.02291

0.237848

2,119

52

166

40.75

0.80743

0.021236

0

0.652174

1

0

0.086873

0.010135

0

1

0

false

0

0.043478

0

0.108696

0

null

0

1

0

1

0

1

0

null

0

8

cdc66fe93d8767b95408a6d4ae1f65ac501fb942

123

py

Python

dem_sim/util/__init__.py

Xorgon/DEMApples

d8a624698965999a60128e84e58c128dd92292c3

[ "MIT" ]

6

2017-11-13T18:09:20.000Z

2021-09-17T13:49:53.000Z

dem_sim/util/__init__.py

Xorgon/DEMApples

d8a624698965999a60128e84e58c128dd92292c3

[ "MIT" ]

null

dem_sim/util/__init__.py

Xorgon/DEMApples

d8a624698965999a60128e84e58c128dd92292c3

[ "MIT" ]

3

2020-05-21T13:45:55.000Z

2021-09-17T13:54:14.000Z

import dem_sim.util.flow_plot import dem_sim.util.particle_trace import dem_sim.util.file_io import dem_sim.util.num_utils

24.6

34

0.869919

24

123

4.125

0.5

0.363636

0.484848

0.646465

0

0.065041

123

4

35

30.75

0.86087

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

7

a8242ec4d7cfce41cf3edeb5e55d12ad782b9428

114

py

Python

AI/svm/main.py

zxpatric/Sandbox

af8b7b633a097de747243a119882fed4779b7c81

[ "MIT" ]

null

AI/svm/main.py

zxpatric/Sandbox

af8b7b633a097de747243a119882fed4779b7c81

[ "MIT" ]

null

AI/svm/main.py

zxpatric/Sandbox

af8b7b633a097de747243a119882fed4779b7c81

[ "MIT" ]

null

# from svm_1 import * # from svm_2 import * # from svm_3 import * from svm_5 import * # from svm_scikit import *

16.285714

26

0.701754

20

114

3.75

0.4

0.466667

0.693333

0

0.044944

0.219298

114

6

27

19

0.797753

0.736842

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

b51f2adf3d6d5e1b3b5d44ccb0cf91db1ab7fe01

215

py

Python

libmodel/django/__init__.py

caser789/libmodel

8a063737ad568d3f9c4f7ddd78680582f71380f4

[ "MIT" ]

1

2019-05-03T07:35:20.000Z

libmodel/django/__init__.py

caser789/libmodel

8a063737ad568d3f9c4f7ddd78680582f71380f4

[ "MIT" ]

null

libmodel/django/__init__.py

caser789/libmodel

8a063737ad568d3f9c4f7ddd78680582f71380f4

[ "MIT" ]

null

from .partition_model import PartitionModel from .utils import static_module from .utils import static_div from .utils import static_lower from .utils import static_upper from .database_router import DatabaseRouter

30.714286

43

0.860465

30

215

5.966667

0.466667

0.201117

0.335196

0.469274

0

0.111628

215

6

44

35.833333

0.937173

0

1

0

true

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

b565a75f237e012a4da8e018c262675e8a4e10b8

299,918

py

Python

app.py

tanveerntu/paktextiles

0e43fcc08f53cac87d784c0325b4be7899bea4db

[ "MIT" ]

null

app.py

tanveerntu/paktextiles

0e43fcc08f53cac87d784c0325b4be7899bea4db

[ "MIT" ]

null

app.py

tanveerntu/paktextiles

0e43fcc08f53cac87d784c0325b4be7899bea4db

[ "MIT" ]

null

import streamlit as st import pandas as pd from plotly import graph_objs as go from plotly.subplots import make_subplots import plotly.express as px from PIL import Image # Use the full page instead of a narrow central column st.set_page_config( page_title = 'Pakistan Textile Exports', page_icon = '✅', layout = 'wide' ) # ---- HIDE STREAMLIT STYLE ---- hide_st_style = """ <style> #MainMenu {visibility: hidden;} footer {visibility: hidden;} header {visibility: hidden;} </style> """ st.markdown(hide_st_style, unsafe_allow_html=True) #from pages import garments, knitwear, textile # import your app modules here st.sidebar.header('Pakistan Textile Exports') page_names = ['Dashboard', #index =0 'Total Textile Exports', #index=1 'Raw Cotton Exports', #'Carded/Combed Cotton Exports', 'Cotton Yarn Exports', 'Non-Cotton Yarn Exports', 'Cotton Cloth Exports', 'Knitwear Exports', 'Bedwear Exports', 'Readymade Garments Exports', 'Towel Exports', 'Tents & Tarpaulines Exports', 'Made-ups excluding Bedwear & Towels', 'Artifical Silk & Synthetics Exports', 'Other Textiles Exports', 'Overall Pakistan Trade', 'Cotton Statistics', ] page = st.sidebar.radio('Navigation', page_names, index=0) #st.write("**The variable 'page' returns:**", page) ######################################## ######################################## if page == 'Cotton Statistics': #importing csv file as dataframe df = pd.read_csv('cotton_districts.csv') #shorten name of a district for better display on chart #df['District'] = df['District'].replace('Shaheed Benazirabad', 'Benazirabad') ######################################## ######################################## #yearly trend chart ######################################## #creating new colum 'Bales_sum' of yearly sum of bales df_yearly = df.groupby(['Year']).agg(Bales_sum=('Bales', 'sum')).reset_index() ############################## ############################## fig_cd = go.Figure() # Add traces fig_cd.add_trace(go.Bar(x=df_yearly['Year'], y=df_yearly['Bales_sum'], name='Cotton Bales', text=df_yearly['Bales_sum'], #text on bars textfont_size=24, #text on bars textfont_family='roboto', textposition='auto', texttemplate='%{text:.3s}', # to text shorten into 3 digits, use '%{text:.3s}' marker_color='#006BA2', #bar colors hovertemplate='%{x} <br>Cotton Bales: %{y}' )) from PIL import Image image = Image.open('logo.png') #st.image(logo.png) fig_cd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=1, #image postion on chart sizex=0.15, sizey=0.15, #image size on chart xanchor="right", yanchor="bottom" )) fig_cd.update_layout( autosize=False, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=40, l=40, r=40), #title="Cotton Production in Pakistan", #title_font=dict(size=30, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="No. of Bales", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', ) fig_cd.update_xaxes(showline=True, linewidth=2, linecolor='black') fig_cd.update_yaxes(showline=True, linewidth=2, linecolor='black') fig_cd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_cd.update_yaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_cd.update_yaxes(title_font=dict(family='Roboto', color='black', size=24)) #fig_cd.update_xaxes(font=dict(color='#111111', size=24, family="roboto, sans-serif")) fig_cd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') #title fig_cd.add_annotation( text="Cotton Production", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="x domain", yref="y domain", x=0, y=1.15, showarrow=False, arrowhead=1) #subtitle fig_cd.add_annotation( text="in Pakistan over the last few years of the closing season", font=dict(family='roboto', color='black', size=24), xref="x domain", yref="y domain", x=0, y=1.08, showarrow=False, arrowhead=1) #datasource fig_cd.add_annotation( text="Source: Pakistan Cotton Ginners Association/National Textile University, Pakistan", font=dict(family='Roboto', color='#758D99', size=20), xref="x domain", yref="y domain", x=0, y=-0.13, showarrow=False, arrowhead=1) st.plotly_chart(fig_cd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ### ####################################### ############################### #cotton exports and imports ############################## df_e = pd.read_csv('yearly_cotton_imports_pbs.csv') df_e['year'] = df_e['year'].astype(str) ############################## fig = go.Figure() # Add traces fig.add_trace(go.Bar( x=df_e["year"], y=df_e["imp_bales"], text=df_e["imp_bales"], marker_color='#ff6b6c', name='Imports' #name on legend )) fig.add_trace(go.Bar( x=df_e["year"], y=df_e["exp_bales"], text=df_e["exp_bales"], marker_color='#3ebcd2', name='Exports' )) fig.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=1, #image postion on chart sizex=0.15, sizey=0.15, #image size on chart xanchor="right", yanchor="bottom" )) fig.update_traces(texttemplate='%{text:.2s}', textposition='auto', textfont_size=24, textfont_family='roboto', textfont_color="#111111") fig.update_layout( autosize=False, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=40, l=40, r=40), xaxis_title='', yaxis_title="No. of Bales", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', ) fig.update_xaxes(showline=True, linewidth=2, linecolor='black') fig.update_yaxes(showline=True, linewidth=2, linecolor='black') fig.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig.update_yaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig.update_yaxes(title_font=dict(family='Roboto', color='black', size=24)) #fig_cd.update_xaxes(font=dict(color='#111111', size=24, family="roboto, sans-serif")) fig.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') #title fig.add_annotation( text="Cotton Exports & Imports", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="x domain", yref="y domain", x=0, y=1.15, showarrow=False, arrowhead=1) #subtitle fig.add_annotation( text="in Pakistan over the last few years of the closing season", font=dict(family='roboto', color='black', size=24), xref="x domain", yref="y domain", x=0, y=1.08, showarrow=False, arrowhead=1) #datasource fig.add_annotation( text="Source: Pakistan Bureau of Statistics/National Textile University, Pakistan", font=dict(family='Roboto', color='#758D99', size=20), xref="x domain", yref="y domain", x=0, y=-0.13, showarrow=False, arrowhead=1) fig.update_layout(legend=dict( orientation="h", font=dict(family='Roboto', color='#758D99', size=16), yanchor="bottom", y=1.02, xanchor="right", x=0.8)) st.plotly_chart(fig, use_container_width=True) # to show Figure; container width true makes fig. size responsive ############################### ################################ #monthly cotton imports #importing csv file as dataframe df_m = pd.read_csv('monthly_cotton_imports_pbs.csv') #calculating year-to-date YTD bales and adding new column for the same df_m['bales_ytd'] = df_m['bales'].cumsum() df_m['usd_ytd'] = df_m['USD'].cumsum() ############## fig = go.Figure() ############### # Add traces fig.add_trace(go.Bar(x=df_m['month'], y=df_m['bales_ytd'], name='Cotton Bales', text=df_m['bales_ytd'], #text on bars textfont_size=24, #text on bars textfont_family='roboto', textposition='auto', texttemplate='%{text:.3s}', # to text shorten into 3 digits, use '%{text:.3s}' marker_color='#006BA2', #bar colors )) fig.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=1, #image postion on chart sizex=0.15, sizey=0.15, #image size on chart xanchor="right", yanchor="bottom" )) ############### #layout fig.update_layout( autosize=False, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=90, l=90, r=40), plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', ) ############### #updates axes fig.update_xaxes(showline=True, linewidth=2, linecolor='black') fig.update_yaxes(showline=True, linewidth=2, linecolor='black') fig.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig.update_yaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig.update_yaxes(title='Cumulative No. of Bales', title_font=dict(family='Roboto', color='black', size=24)) fig.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig.add_annotation( text="Cotton Imports", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="x domain", yref="y domain", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig.add_annotation( text="in Pakistan in the current financial year 2021-22", font=dict(family='roboto', color='black', size=24), xref="x domain", yref="y domain", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig.add_annotation( text="Source: Pakistan Bureau of Statistics/National Textile University, Pakistan", font=dict(family='Roboto', color='#758D99', size=20), xref="x domain", yref="y domain", x=0, y=-0.18, showarrow=False, arrowhead=1) ###################### #show figure in streamlit web app st.plotly_chart(fig, use_container_width=True) # to show Figure; container width true makes fig. size responsive ############################## ############################## ############## fig = go.Figure() ############### # Add traces fig.add_trace(go.Bar(x=df_m['month'], y=df_m['usd_ytd'], name='Cotton Bales', text=df_m['usd_ytd'], #text on bars textfont_size=24, #text on bars textfont_family='roboto', textposition='auto', texttemplate='%{text:.3s}', # to text shorten into 3 digits, use '%{text:.3s}' marker_color='#ff6b6c', #bar colors )) fig.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=1, #image postion on chart sizex=0.15, sizey=0.15, #image size on chart xanchor="right", yanchor="bottom" )) ############### #layout fig.update_layout( autosize=False, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=90, l=90, r=40), plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', ) ############### #updates axes fig.update_xaxes(showline=True, linewidth=2, linecolor='black') fig.update_yaxes(showline=True, linewidth=2, linecolor='black') fig.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig.update_yaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig.update_yaxes(title='Cumulative US$', title_font=dict(family='Roboto', color='black', size=24)) fig.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig.add_annotation( text="Cost of Cotton Imports", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="x domain", yref="y domain", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig.add_annotation( text="Cumulative price paid for cotton imports till recent month)", font=dict(family='roboto', color='black', size=24), xref="x domain", yref="y domain", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig.add_annotation( text="Source: Pakistan Bureau of Statistics/National Textile University, Pakistan", font=dict(family='Roboto', color='#758D99', size=20), xref="x domain", yref="y domain", x=0, y=-0.18, showarrow=False, arrowhead=1) ###################### #show figure in streamlit web app st.plotly_chart(fig, use_container_width=True) # to show Figure; container width true makes fig. size responsive ############################## ############################## ############################## #grouping by province ############################### df_punjab = df[df['Province'] == 'Punjab'] df_punjab = df_punjab.groupby(['Year']).agg({'Bales':'sum'}).reset_index() df_sindh = df[df['Province'] == 'Sindh'] df_sindh = df_sindh.groupby(['Year']).agg({'Bales':'sum'}).reset_index() df_baluchistan = df[df['Province'] == 'Baluchistan'] df_baluchistan = df_baluchistan.groupby(['Year']).agg({'Bales':'sum'}).reset_index() fig = go.Figure() fig.add_trace(go.Bar( x=df_punjab["Year"], y=df_punjab["Bales"], text=df_punjab["Bales"], marker_color='#ff6b6c', name='Punjab' #name on legend )) fig.add_trace(go.Bar( x=df_sindh["Year"], y=df_sindh["Bales"], text=df_sindh["Bales"], marker_color='#3ebcd2', name='Sindh' )) fig.add_trace(go.Bar( x=df_baluchistan["Year"], y=df_baluchistan["Bales"], text=df_baluchistan["Bales"], marker_color='#006BA2', name='Baluchistan' )) fig.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=1, #image postion on chart sizex=0.15, sizey=0.15, #image size on chart xanchor="right", yanchor="bottom" )) fig.update_traces(texttemplate='%{text:.2s}', textposition='auto', textfont_size=24, textfont_family='roboto', textfont_color="#111111") fig.update_layout( autosize=True, height=650, width=1050, margin=dict(t=100, b=120, l=40, r=40), plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', bargap=0.2, #value can be An int or float in the interval [0, 1] ) fig.update_xaxes(showline=True, linewidth=2, linecolor='black') fig.update_yaxes(showline=True, linewidth=2, linecolor='black') fig.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig.update_yaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig.update_yaxes(title_font=dict(family='Roboto', color='black', size=24)) #fig_cd.update_xaxes(font=dict(color='#111111', size=24, family="roboto, sans-serif")) fig.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') fig.update_yaxes(title="No. of Bales", title_font=dict(size=25, color='#111111', family="roboto"), ) #title fig.add_annotation( text="Cotton Production", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="x domain", yref="y domain", x=0, y=1.19, showarrow=False, arrowhead=1) #subtitle fig.add_annotation( text=f"in different Pakistani provinces over the last few years", font=dict(family='roboto', color='black', size=24), xref="x domain", yref="y domain", x=0, y=1.11, showarrow=False, arrowhead=1) fig.add_annotation( text="Source: Pakistan Cotton Ginners Association/National Textile University, Pakistan", font=dict(family='Roboto', color='#758D99', size=20), xref="x domain", yref="y domain", x=0, y=-0.24, showarrow=False, arrowhead=1) fig.update_layout(legend=dict( orientation="h", font=dict(family='Roboto', color='#758D99', size=16), yanchor="bottom", y=1.08, xanchor="right", x=0.8)) st.plotly_chart(fig, use_container_width=True) # to show Figure; container width true makes fig. size responsive ############################ ############################ # district-wise chart ########################### #year = df["Year"] #latest_year = year.max() #filter data for latest_year df_latest_year = df[df['Period'] == '2021-22'] fig = go.Figure() # Add traces fig.add_trace(go.Bar(x=df_latest_year['District'], y=df_latest_year['Bales'], name='Cotton Bales', text=df_latest_year['Bales'], #text on bars textfont_size=24, #text on bars textfont_family='roboto', texttemplate='%{text:.3s}', # to text shorten into 3 digits, use '%{text:.3s}' marker_color='#006BA2', #bar colors )) fig.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=1, #image postion on chart sizex=0.15, sizey=0.15, #image size on chart xanchor="right", yanchor="bottom" )) fig.update_layout( autosize=False, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=40, l=40, r=40), #title="Cotton Production in Pakistan", #title_font=dict(size=30, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="No. of Bales", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', ) fig.update_xaxes(showline=True, linewidth=2, linecolor='black') fig.update_yaxes(showline=True, linewidth=2, linecolor='black') fig.update_xaxes(tickangle=90, tickfont=dict(family='Roboto', color='black', size=24)) fig.update_yaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig.update_yaxes(title_font=dict(family='Roboto', color='black', size=24)) #fig_cd.update_xaxes(font=dict(color='#111111', size=24, family="roboto, sans-serif")) fig.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') fig.update_xaxes({'categoryorder':'total descending'}) #title fig.add_annotation( text="Cotton Production", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="x domain", yref="y domain", x=0, y=1.22, showarrow=False, arrowhead=1) #subtitle fig.add_annotation( text=f"in different Pakistani districts during 2020-21 season", font=dict(family='roboto', color='black', size=24), xref="x domain", yref="y domain", x=0, y=1.11, showarrow=False, arrowhead=1) fig.add_annotation( text="Source: Pakistan Cotton Ginners Association/National Textile University, Pakistan", font=dict(family='Roboto', color='#758D99', size=20), xref="x domain", yref="y domain", x=0, y=-0.75, showarrow=False, arrowhead=1) st.plotly_chart(fig, use_container_width=True) # to show Figure; container width true makes fig. size responsive ######################## ######################## # montlhy cotton arrivals chart ########################### ################# df_cotton_arrivals = pd.read_csv('cotton_arrivals.csv') fig = go.Figure() fig.add_trace(go.Scatter( x=df_cotton_arrivals["Date"], y=df_cotton_arrivals["2018-19"], name="2018-19", text=df_cotton_arrivals['2018-19'], texttemplate='%{text:.3s}', #text shorten into 3 digits mode="markers+lines", textposition="bottom right", textfont=dict(family="roboto, sans-serif", size=18, color="#eca220"), marker=dict(size=8, color="#eca220"), line=dict(width=2, color="#eca220"), )) fig.add_trace(go.Scatter( x=df_cotton_arrivals["Date"], y=df_cotton_arrivals["2019-20"], name="2019-20", text=df_cotton_arrivals['2019-20'], texttemplate='%{text:.3s}', #text shorten into 3 digits mode="markers+lines", textposition="bottom right", textfont=dict(family="roboto, sans-serif", size=18, color="#b4bb3b"), marker=dict(size=8, color="#b4bb3b"), line=dict(width=2, color="#b4bb3b"), )) fig.add_trace(go.Scatter( x=df_cotton_arrivals["Date"], y=df_cotton_arrivals["2020-21"], name="2020-21", text=df_cotton_arrivals['2020-21'], texttemplate='%{text:.3s}', #text shorten into 3 digits mode="markers+lines", textposition="bottom right", textfont=dict(family="roboto, sans-serif", color="#963c4c", size=18), marker=dict(size=8, color="#963c4c"), line=dict(width=2, color="#963c4c"), )) fig.add_trace(go.Scatter( x=df_cotton_arrivals["Date"], y=df_cotton_arrivals["2021-22"], name="2021-22", text=df_cotton_arrivals['2021-22'], texttemplate='%{text:.3s}', # to text shorten into 3 digits, use '%{text:.3s}' mode="markers+lines+text", textposition="bottom right", textfont=dict(family="fjalla one, sans-serif", color="#106ea0", size=20), marker=dict(size=12, color="#106ea0"), line=dict(width=5, color="#106ea0") )) fig.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=1, #image postion on chart sizex=0.15, sizey=0.15, #image size on chart xanchor="right", yanchor="bottom" )) fig.update_layout( autosize=True, height=650, width=1050, margin=dict(t=90, b=120, l=40, r=40), plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', bargap=0.2, #value can be An int or float in the interval [0, 1] ) fig.update_xaxes(showline=True, linewidth=2, linecolor='black') fig.update_yaxes(showline=True, linewidth=2, linecolor='black') fig.update_xaxes(tickangle=90, tickfont=dict(family='Roboto', color='black', size=24)) fig.update_yaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig.update_yaxes(title_font=dict(family='Roboto', color='black', size=24)) #fig_cd.update_xaxes(font=dict(color='#111111', size=24, family="roboto, sans-serif")) fig.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') fig.update_yaxes(title="Cumulative number of bales", title_font=dict(size=25, color='#111111', family="roboto"), ) #title fig.add_annotation( text="Monthly Cotton Arrival", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="x domain", yref="y domain", x=0, y=1.19, showarrow=False, arrowhead=1) #subtitle fig.add_annotation( text=f"in Pakistani factories", font=dict(family='roboto', color='black', size=24), xref="x domain", yref="y domain", x=0, y=1.11, showarrow=False, arrowhead=1) fig.add_annotation( text="Source: Pakistan Cotton Ginners Association/National Textile University, Pakistan", font=dict(family='Roboto', color='#758D99', size=20), xref="x domain", yref="y domain", x=0, y=-0.24, showarrow=False, arrowhead=1) fig.update_layout(legend=dict( orientation="h", font=dict(family='Roboto', color='#758D99', size=16), yanchor="bottom", y=1.02, xanchor="right", x=0.75)) st.plotly_chart(fig, use_container_width=True) # to show Figure; container width true makes fig. size responsive ############################### ############################## #Historical cotton data ######################### ############################## df_h = pd.read_csv('cotton_historical.csv') df_a = pd.read_csv('cotton_area.csv') fig = go.Figure() # Add traces fig.add_trace(go.Scatter( x=df_h["Year"], y=df_h["Bales"], name="", #text=df_cotton_arrivals['2021-22'], #texttemplate='%{text:.3s}', # to text shorten into 3 digits, use '%{text:.3s}' mode="markers+lines", #textposition="bottom right", #textfont=dict(family="fjalla one, sans-serif", color="#106ea0", size=20), marker=dict(size=12, color="#106ea0"), line=dict(width=5, color="#106ea0"), showlegend=False )) fig.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=1, #image postion on chart sizex=0.15, sizey=0.15, #image size on chart xanchor="right", yanchor="bottom" )) fig.update_layout( autosize=False, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=40, l=40, r=40), #title="Cotton Production in Pakistan", #title_font=dict(size=30, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="No. of Bales", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', ) fig.update_xaxes(showline=True, linewidth=2, linecolor='black') fig.update_yaxes(showline=True, linewidth=2, linecolor='black') fig.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig.update_yaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig.update_yaxes(title_font=dict(family='Roboto', color='black', size=24)) #fig_cd.update_xaxes(font=dict(color='#111111', size=24, family="roboto, sans-serif")) fig.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') #adding range buttons fig.update_xaxes( rangeslider_visible = False, rangeselector = dict( buttons = list([ dict(count = 1, label = '1Y', step = 'year', stepmode = 'backward'), dict(count = 2, label = '2Y', step = 'year', stepmode = 'backward'), dict(count = 5, label = '5Y', step = 'year', stepmode = 'backward'), #dict(step = 'all') ]))) #title fig.add_annotation( text="Cotton Production in Pakistan", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="x domain", yref="y domain", x=0, y=1.15, showarrow=False, arrowhead=1) #subtitle fig.add_annotation( text="since 1947-48 season", font=dict(family='roboto', color='black', size=24), xref="x domain", yref="y domain", x=0, y=1.08, showarrow=False, arrowhead=1) #datasource fig.add_annotation( text="Source: Pakistan Cotton Ginners Association/Karachi Cotton Association/National Textile University, Pakistan", font=dict(family='Roboto', color='#758D99', size=20), xref="x domain", yref="y domain", x=0, y=-0.13, showarrow=False, arrowhead=1) #Adding only the last date point value/text fig.add_trace(go.Scatter(x=[df_h['Year'].iloc[-1]], y=[df_h['Bales'].iloc[-1]], text=[df_h['Bales'].iloc[-1]], name='', mode='markers+text', marker=dict(color='red', size=14), textposition='top right', textfont=dict(family="fjalla one, sans-serif", color="#006BA2", size=18), texttemplate='%{text:.3s}', #text shorten into 3 digits showlegend=False)) #Adding value/text at year 2005, which is at index number 57 fig.add_trace(go.Scatter(x=[df_h['Year'].iloc[57]], y=[df_h['Bales'].iloc[57]], text=[df_h['Bales'].iloc[57]], name='', mode='markers+text', marker=dict(color='red', size=14), textposition='middle right', textfont=dict(family="fjalla one, sans-serif", color="#006BA2", size=18), texttemplate='%{text:.3s}', #text shorten into 3 digits showlegend=False)) st.plotly_chart(fig, use_container_width=True) # to show Figure; container width true makes fig. size responsive ########################################## ############################################ #cotton area df_a = pd.read_csv('cotton_area.csv') fig = go.Figure() # Add traces fig.add_trace(go.Scatter( x=df_a["year"], y=df_a["total_acres"], name="", line=dict(width=2, color="red"), fill='tozeroy', showlegend=False )) fig.add_trace(go.Scatter( x=df_a["year"], y=df_a["punjab_acres"], name="", line=dict(width=2, color="#106ea0"), fill='tozeroy', showlegend=False )) fig.add_trace(go.Scatter( x=df_a["year"], y=df_a["sindh_acres"], name="", line=dict(width=2, color="green"), fill='tozeroy', showlegend=False )) fig.add_trace(go.Scatter( x=df_a["year"], y=df_a["kpk_acres"], name="", line=dict(width=2, color="#106ea0"), fill='tozeroy', showlegend=False )) fig.add_trace(go.Scatter( x=df_a["year"], y=df_a["baluchistan_acres"], name="", line=dict(width=2, color="yellow"), fill='tozeroy', showlegend=False )) fig.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=1, #image postion on chart sizex=0.15, sizey=0.15, #image size on chart xanchor="right", yanchor="bottom" )) fig.update_layout( autosize=False, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=40, l=40, r=40), #title="Cotton Production in Pakistan", #title_font=dict(size=30, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="No. of Acres", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', ) fig.update_xaxes(showline=True, linewidth=2, linecolor='black') fig.update_yaxes(showline=True, linewidth=2, linecolor='black') fig.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig.update_yaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig.update_yaxes(title_font=dict(family='Roboto', color='black', size=24)) #fig_cd.update_xaxes(font=dict(color='#111111', size=24, family="roboto, sans-serif")) fig.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') #adding range buttons #title fig.add_annotation( text="Cotton Production Area in Pakistan", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="x domain", yref="y domain", x=0, y=1.15, showarrow=False, arrowhead=1) #subtitle fig.add_annotation( text="since 1947-48 season", font=dict(family='roboto', color='black', size=24), xref="x domain", yref="y domain", x=0, y=1.08, showarrow=False, arrowhead=1) #datasource fig.add_annotation( text="Source: Agriculture Statistics of Pakistan/Agriculture Marketing Information Service, Punjab", font=dict(family='Roboto', color='#758D99', size=20), xref="x domain", yref="y domain", x=0, y=-0.13, showarrow=False, arrowhead=1) #Adding only the last date point value/text fig.add_trace(go.Scatter(x=[df_a['year'].iloc[-1]], y=[df_a['total_acres'].iloc[-1]], text=[df_a['total_acres'].iloc[-1]], name='', mode='markers+text', marker=dict(color='red', size=14), textposition='bottom left', textfont=dict(family="fjalla one, sans-serif", color="white", size=18), texttemplate='Total:%{text:.3s}', #text shorten into 3 digits showlegend=False)) fig.add_trace(go.Scatter(x=[df_a['year'].iloc[-1]], y=[df_a['punjab_acres'].iloc[-1]], text=[df_a['punjab_acres'].iloc[-1]], name='', mode='markers+text', marker=dict(color='red', size=14), textposition='bottom left', textfont=dict(family="fjalla one, sans-serif", color="white", size=18), texttemplate='Punjab:%{text:.3s}', #text shorten into 3 digits showlegend=False)) fig.add_trace(go.Scatter(x=[df_a['year'].iloc[-1]], y=[df_a['sindh_acres'].iloc[-1]], text=[df_a['sindh_acres'].iloc[-1]], name='', mode='markers+text', marker=dict(color='red', size=14), textposition='bottom left', textfont=dict(family="fjalla one, sans-serif", color="white", size=18), texttemplate='Sindh:%{text:.3s}', #text shorten into 3 digits showlegend=False)) fig.add_trace(go.Scatter(x=[df_a['year'].iloc[-1]], y=[df_a['baluchistan_acres'].iloc[-1]], text=[df_a['baluchistan_acres'].iloc[-1]], name='', mode='markers+text', marker=dict(color='red', size=14), textposition='middle left', textfont=dict(family="fjalla one, sans-serif", color="white", size=18), texttemplate='Baluchistan:%{text:.3s}', #text shorten into 3 digits showlegend=False)) fig.add_trace(go.Scatter(x=[df_a['year'].iloc[-1]], y=[df_a['kpk_acres'].iloc[-1]], text=[df_a['kpk_acres'].iloc[-1]], name='', mode='markers+text', marker=dict(color='red', size=14), textposition='bottom left', textfont=dict(family="fjalla one, sans-serif", color="black", size=18), texttemplate='kpk:%{text:.3s}', #text shorten into 3 digits showlegend=False)) st.plotly_chart(fig, use_container_width=True) # to show Figure; container width true makes fig. size responsive ############################### ############################## #correlation matric df_cor = pd.read_csv('crops_area_correlation_data.csv') corr = df_cor.corr() trace = go.Heatmap(z=corr.values, x=corr.index.values, y=corr.columns.values, xgap = 1, # Sets the horizontal gap (in pixels) between bricks ygap = 1, ) title = 'Crop Correlation Matrix' layout = go.Layout( title_text=title, title_x=0.5, xaxis_showgrid=False, yaxis_showgrid=False, yaxis_autorange='reversed', autosize=False, height=650, width=1050, margin=dict(t=90, b=40, l=40, r=40), plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(family="fjalla one, sans-serif", color="black", size=18), ) fig=go.Figure(data=[trace], layout=layout) fig.update_xaxes(tickangle=90, tickfont=dict(family='Roboto', color='black', size=24)) #st.plotly_chart(fig, use_container_width=True) # to show Figure; container width true makes fig. size responsive ################## import seaborn as sns import seaborn as sns import matplotlib.pyplot as plt fig, ax = plt.subplots(figsize=(16, 8)) sns.set(font_scale=1) # font size 2 set size for all seaborn graph labels heatmap = sns.heatmap(df_cor.corr(), ax=ax, vmin=-1, vmax=1, annot=True, annot_kws={"size": 20}, cmap='BrBG') heatmap.set_title('Correlation Heatmap', fontdict={'fontsize':24}, pad=12); st.write(fig) ########################### ############################ fig = plt.figure(figsize=(16, 8)) heatmap = sns.heatmap(df_cor.corr(), vmin=-1, vmax=1, annot=True) heatmap.set_title('Correlation Heatmap', fontdict={'fontsize':18}, pad=12); # save heatmap as .png file # dpi - sets the resolution of the saved image in dots/inches # bbox_inches - when set to 'tight' - does not allow the labels to be cropped plt.savefig('heatmap.png', dpi=300, bbox_inches='tight') #st.write(fig) ############# ########################### ######################## #monthly cotton imports ############################## #Cotton prices ############################# import yfinance as yf from datetime import datetime, timedelta #data = yf.download(tickers=stock_price, period = ‘how_many_days’, interval = ‘how_long_between_each_check’, rounding= bool) #data = yf.download(tickers='CT=F', period = '5Y', interval = '1D', rounding= True) data = yf.download(tickers='CT=F', start = '2017-01-01', end = datetime.now().date(), rounding= True) #data data= data.reset_index() # to show date as column header #data ## getting the live ticker price # import stock_info module from yahoo_fin from yahoo_fin import stock_info as si #to get live price of ticker/cotton CT=F price = si.get_live_price('CT=F') prev_close = data.Close.iloc[-2] #iloc[-2] is second last row of res_df ; iloc[0] is first row ## fig = go.Figure() fig.add_trace(go.Scatter(x=data['Date'], y=data['Close'], name = '', texttemplate='%{text:.2s}', # to shorten text into 3 digits, use '%{text:.3s}' )) fig.update_traces(hovertemplate='Date: %{x} <br>Price: %{y} cents per pound') #<br> adds space or shifts to next line; x & y is repected axis value; fig.add_trace(go.Indicator( domain={"x": [0, 1], "y": [0.6, 1]}, value=price, mode="number+delta", number={"font":{"size":50, "color":'#111111', "family":"roboto"}}, title={"text": "Current Price in cents per pound"}, title_font=dict(size=25, color='#111111', family="roboto"), delta={"reference": prev_close}, )) fig.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=1, #image postion on chart sizex=0.15, sizey=0.15, #image size on chart xanchor="right", yanchor="bottom" )) fig.update_yaxes(title_text = 'Cents Per Pound', tickprefix = '') #fig.update_xaxes(showspikes=True, spikecolor="red", spikesnap="cursor", spikemode="across", spikethickness=3) #xaxis spike on hover #fig.update_yaxes(showspikes=True, spikecolor="red", spikesnap="cursor", spikemode="across", spikethickness=3) #yais spike on hover fig.update_layout( autosize=True, height=650, width=1050, margin=dict(t=90, b=120, l=40, r=40), plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=20, family="roboto, sans-serif"), bargap=0.2, #value can be An int or float in the interval [0, 1] ) fig.update_xaxes(showline=True, linewidth=2, linecolor='black') fig.update_yaxes(showline=True, linewidth=2, linecolor='black') fig.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig.update_yaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig.update_yaxes(title_font=dict(family='Roboto', color='black', size=24)) #fig_cd.update_xaxes(font=dict(color='#111111', size=24, family="roboto, sans-serif")) fig.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') fig.update_yaxes(title="Cents Per Pound", title_font=dict(size=25, color='#111111', family="roboto"), ) fig.update_xaxes( rangeslider_visible = False, rangeselector = dict( buttons = list([ dict(count = 1, label = '1W', step = 'day', stepmode = 'backward'), dict(count = 1, label = '1M', step = 'month', stepmode = 'backward'), dict(count = 6, label = '6M', step = 'month', stepmode = 'backward'), dict(count = 1, label = 'YTD', step = 'year', stepmode = 'todate'), dict(count = 1, label = '1Y', step = 'year', stepmode = 'backward'), dict(count = 2, label = '2Y', step = 'year', stepmode = 'backward'), dict(count = 5, label = '5Y', step = 'year', stepmode = 'backward'), #dict(step = 'all') ]))) #title fig.add_annotation( text="Cotton Rates/ICE Futures", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="x domain", yref="y domain", x=0, y=1.19, showarrow=False, arrowhead=1) fig.add_annotation( text="Source: Yahoo Finance/National Textile University", font=dict(family='Roboto', color='#111111', size=20), xref="x domain", yref="y domain", x=0, y=-0.24, showarrow=False, arrowhead=1) st.plotly_chart(fig, use_container_width=True) # to show Figure; container width true makes fig. size responsive ########################### ########################### #cotton map of Pakistan ########################### import json pak_districts = json.load(open("pakistan_districts.geojson", 'r')) district_id_map = {} for feature in pak_districts["features"]: feature["id"] = feature["properties"]["objectid"] district_id_map[feature['properties']['districts']] = feature['id'] df['id']=df['District'].apply(lambda x:district_id_map[x]) #st.title("Cotton Map of Pakistan") fig = go.Figure(go.Choroplethmapbox(geojson=pak_districts, locations=df.id, z=df.Bales, text= df['District'], hoverinfo= 'text+z', reversescale=True, )) fig.update_layout(mapbox_style="stamen-terrain", mapbox_zoom=5.0, mapbox_center = {"lat": 30.3753, "lon": 69.3451}) fig.update_traces(text=df['District']) fig.update_layout( autosize=True, height=650, width=1400, ) fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0}) ##### #st.plotly_chart(fig) ###################### ####################### st.title("Cotton Map of Pakistan") #satellite-streets ############# fig = px.scatter_mapbox(df, lat="Lat", lon="Long", hover_name="District", hover_data=["District", "Bales"], color_discrete_sequence=["Red"], size="Bales", animation_frame="Year", zoom=5, height=300 ) fig.update_layout(mapbox_style="open-street-map") fig.update_layout( autosize=True, height=700, width=1400, ) fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0}) st.plotly_chart(fig, use_container_width=True) ######################################## elif page == 'Overall Pakistan Trade': df = pd.read_csv('paktrade_pbs.csv') ############## fig = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.65,0.35]) ############### # Add traces fig.add_trace(go.Scatter( x=df["year"], y=df["export_US$B"], name="Exports", text=df['export_US$B'], texttemplate='%{text:.3s}', # to text shorten into 3 digits, use '%{text:.3s}' mode="markers+lines", textposition="bottom right", textfont=dict(family="fjalla one, sans-serif", color="green", size=20), marker=dict(size=12, color="green"), line=dict(width=5, color="green")), row=1, col=1) # Add traces fig.add_trace(go.Scatter( x=df["year"], y=df["import_US$B"], name="Imports", text=df['import_US$B'], texttemplate='%{text:.3s}', # to text shorten into 3 digits, use '%{text:.3s}' mode="markers+lines", textposition="bottom right", textfont=dict(family="fjalla one, sans-serif", color="red", size=20), marker=dict(size=12, color="red"), line=dict(width=5, color="red")), row=1, col=1) # Plot MACD trace on 3rd row #val = df['balance_US$B'] #colors = ['green' if val >= 0 # else 'red' for val in df['balance_US$B']] fig.add_trace(go.Bar(x=df['year'], y=df['balance_US$B'], name='Trade Balance', #text=df['balance_US$B'], #text on bars #textfont_size=24, #text on bars #textfont_family='roboto', #texttemplate='%{text:.3s}', # to text shorten into 3 digits, use '%{text:.3s}' marker_color='red', #bar colors ), row=2, col=1) ############### image = Image.open('logo.png') #st.image(logo.png) fig.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) #layout fig.update_layout( autosize=False, height=650, width=1050, #legend_traceorder="reversed", margin=dict(t=60, b=120, l=40, r=40), plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', ) ############### #updates axes fig.update_xaxes(showline=True, linewidth=8, linecolor='black', row=1, col=1) fig.update_yaxes(showline=True, linewidth=2, linecolor='black', row=1, col=1) fig.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1) fig.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig.update_yaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig.update_yaxes(side='right', title='US$ Billion', title_font=dict(family='Roboto', color='black', size=20), row=1, col=1) fig.update_yaxes(side='right', title='Trade Balance', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99', row=1, col=1) fig.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99', row=2, col=1) ############### #title fig.add_annotation( text="Pakistan Exports and Imports", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="x domain", yref="y domain", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig.add_annotation( text="1950-51 to 2020-21", font=dict(family='roboto', color='black', size=24), xref="x domain", yref="y domain", x=0, y=1.06, showarrow=False, arrowhead=1) #data reference fig.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="x domain", yref="y domain", x=0, y=-0.9, showarrow=False, arrowhead=1) #Adding only the last date point value/text fig.add_trace(go.Scatter(x=[df['year'].iloc[-1]], y=[df['export_US$B'].iloc[-1]], text=[df['export_US$B'].iloc[-1]], name='', mode='markers+text', marker=dict(color='green', size=14), textposition='top center', textfont=dict(family="fjalla one, sans-serif", color="green", size=20), texttemplate='$%{text:.3s}B', #text shorten into 3 digits showlegend=False)) #Adding only the last date point value/text fig.add_trace(go.Scatter(x=[df['year'].iloc[-1]], y=[df['import_US$B'].iloc[-1]], text=[df['import_US$B'].iloc[-1]], name='', mode='markers+text', marker=dict(color='red', size=14), textposition='top center', textfont=dict(family="fjalla one, sans-serif", color="red", size=20), texttemplate='$%{text:.3s}B', #text shorten into 3 digits showlegend=False)) #Adding only the last date point value/text fig.add_trace(go.Scatter(x=[df['year'].iloc[-1]], y=[df['balance_US$B'].iloc[-1]], text=[df['balance_US$B'].iloc[-1]], name='', mode='markers+text', marker=dict(color='red', size=14), textposition='bottom center', textfont=dict(family="fjalla one, sans-serif", color="red", size=20), texttemplate='$%{text:.3s}B', #text shorten into 3 digits showlegend=False), row=2, col=1) #legend fig.update_layout(legend=dict( orientation="h", font=dict(family='Roboto', color='#758D99', size=16), yanchor="bottom", y=1.02, xanchor="right", x=1)) ###################### #show figure in streamlit web app st.plotly_chart(fig, use_container_width=True) # to show Figure; container width true makes fig. size responsive #config={'responsive': True} ############################## ############################## ####################################### ######################################## ######################################## #data df1 = pd.read_csv('monthly_trade.csv') #calculating year-to-date YTD bales and adding new column for the same df1['imports_ytd_21_22'] = df1['imports_21_22B'].cumsum() df1['imports_ytd_20_21'] = df1['imports_20_21B'].cumsum() df1['exports_ytd_20_21'] = df1['exports_20_21B'].cumsum() df1['exports_ytd_21_22'] = df1['exports_21_22B'].cumsum() df1['balance_ytd_20_21'] = df1['balance_20_21B'].cumsum() df1['balance_ytd_21_22'] = df1['balance_21_22B'].cumsum() ############## #fig = go.Figure() # add subplot properties when initializing fig variable fig = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.65,0.35]) ############### # Add traces fig.add_trace(go.Scatter( x=df1["month"], y=df1["imports_ytd_21_22"], name="Imports 21-22", text=df1['imports_ytd_21_22'], texttemplate='%{text:.3s}B', # to text shorten into 3 digits, use '%{text:.3s}' mode="markers+lines+text", textposition="bottom right", textfont=dict(family="fjalla one, sans-serif", color="red", size=20), marker=dict(size=12, color="red"), line=dict(width=5, color="red")), row=1, col=1) fig.add_trace(go.Scatter( x=df1["month"], y=df1["imports_ytd_20_21"], name="Imports 20-21", text=df1['imports_ytd_20_21'], texttemplate='%{text:.3s}B', # to text shorten into 3 digits, use '%{text:.3s}' mode="markers+lines+text", textposition="bottom right", textfont=dict(family="fjalla one, sans-serif", color="brown", size=20), marker=dict(size=12, color="brown"), line=dict(width=5, color="brown")), row=1, col=1) fig.add_trace(go.Scatter( x=df1["month"], y=df1["exports_ytd_20_21"], name="Exports 20-21", text=df1['exports_ytd_20_21'], texttemplate='%{text:.3s}B', # to text shorten into 3 digits, use '%{text:.3s}' mode="markers+lines+text", textposition="bottom right", textfont=dict(family="fjalla one, sans-serif", color="lightgreen", size=20), marker=dict(size=12, color="lightgreen"), line=dict(width=5, color="lightgreen")), row=1, col=1) fig.add_trace(go.Scatter( x=df1["month"], y=df1["exports_ytd_21_22"], name="Exports 21-22", text=df1['exports_ytd_21_22'], texttemplate='%{text:.3s}B', # to text shorten into 3 digits, use '%{text:.3s}' mode="markers+lines+text", textposition="bottom right", textfont=dict(family="fjalla one, sans-serif", color="green", size=20), marker=dict(size=12, color="green"), line=dict(width=5, color="green")), row=1, col=1) # Plot MACD trace on 3rd row #val = df['balance_US$B'] #colors = ['green' if val >= 0 # else 'red' for val in df['balance_US$B']] fig.add_trace(go.Scatter(x=df1['month'], y=df1['balance_ytd_20_21'], name='Trade Balance 20-21', text=df1['balance_ytd_20_21'], texttemplate='%{text:.3s}B', # to text shorten into 3 digits, use '%{text:.3s}' mode="markers+lines+text", textposition="top right", textfont=dict(family="fjalla one, sans-serif", color="lightblue", size=20), marker=dict(size=12, color="lightblue"), line=dict(width=5, color="lightblue")), row=2, col=1) fig.add_trace(go.Scatter(x=df1['month'], y=df1['balance_ytd_21_22'], name='Trade Balance 21-22', text=df1['balance_ytd_21_22'], texttemplate='%{text:.3s}B', # to text shorten into 3 digits, use '%{text:.3s}' mode="markers+lines+text", textposition="top right", textfont=dict(family="fjalla one, sans-serif", color="orange", size=20), marker=dict(size=12, color="orange"), line=dict(width=5, color="orange")), row=2, col=1) ############### image = Image.open('logo.png') #st.image(logo.png) fig.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=1, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) #layout fig.update_layout( autosize=False, height=650, width=1050, #legend_traceorder="reversed", margin=dict(t=80, b=110, l=40, r=40), plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', ) ############### #updates axes fig.update_xaxes(showline=True, linewidth=8, linecolor='black', row=1, col=1) fig.update_yaxes(showline=True, linewidth=2, linecolor='black', row=1, col=1) fig.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1) fig.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig.update_yaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig.update_yaxes(side='right', title='US$ Billion', title_font=dict(family='Roboto', color='black', size=20), row=1, col=1) fig.update_yaxes(side='right', title='Trade Balance', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99', row=1, col=1) fig.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99', row=2, col=1) ############### #title fig.add_annotation( text="Pakistan Exports and Imports", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="x domain", yref="y domain", x=0, y=1.21, showarrow=False, arrowhead=1) #subtitle fig.add_annotation( text="2020-21 vs. 2021-22 (cumulative figures till recent month)", font=dict(family='roboto', color='black', size=24), xref="x domain", yref="y domain", x=0, y=1.09, showarrow=False, arrowhead=1) #data reference fig.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="x domain", yref="y domain", x=0, y=-0.9, showarrow=False, arrowhead=1) #legend fig.update_layout(legend=dict( orientation="h", font=dict(family='Roboto', color='#758D99', size=16), yanchor="bottom", y=-0.16, xanchor="right", x=1)) ###################### #show figure in streamlit web app st.plotly_chart(fig, use_container_width=True) # to show Figure; container width true makes fig. size responsive ############################## ############################## elif page == 'Raw Cotton Exports': ##################################### ##################################### # cotton chart US$ df = pd.read_csv('monthly_textile_exports_pbs.csv') df['date'] = pd.to_datetime(df['date'], infer_datetime_format=True) df['year'] = df['date'].dt.year #creates a year column out of datetime columns df['month'] = df['date'].dt.month #creates a month column out of datetime columns df['year'] = df['year'].astype('string') #converting year column into string for filtering df['month'] = df['month'].astype('string') #converting year column into string for filtering df['Fiscal Year'] = df['date'].dt.to_period('Q-JUN').dt.qyear.apply(lambda x: str(x-1) + "-" + str(x)) #adding month column df['month'] = df['date'].dt.strftime('%b') #creating month names column #filtering data of fiscal year 2021-22 df_cotton = df.loc[df['category'].isin(['Raw Cotton'])] #calculating year-to-date YTD exports df_cotton['Exports_YTD'] = df_cotton.groupby(['Fiscal Year'])['Exports_US$'].cumsum() df_cotton['pct_change_yoy'] = df_cotton.groupby(['month'])['Exports_YTD'].pct_change()*100 #filtering data of fiscal year 2020-21 df_cotton_2020_21 = df_cotton.loc[df_cotton['Fiscal Year'].isin(['2020-2021'])] df_cotton_2021_22 = df_cotton.loc[df_cotton['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_cotton_2020_21['month'], y=df_cotton_2020_21['Exports_YTD'], name='Exports in 2020-21', text=df_cotton_2020_21['Exports_YTD'], textposition='auto', texttemplate='%{text:,}', hovertemplate='Exports to date: %{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_cotton_2021_22['month'], y=df_cotton_2021_22['Exports_YTD'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Exports in 2021-22', text=df_cotton_2021_22['Exports_YTD'], textposition='bottom right', texttemplate="%{text:,}", line=dict(color='Green', width=4), hovertemplate='Exports to date: %{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_cotton_2021_22['month'], y=df_cotton_2021_22['pct_change_yoy'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_cotton_2021_22['pct_change_yoy'], textposition='middle right', texttemplate="%{text:.3s}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='Cumulative Exports (US$)', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Pakistan Raw Cotton Exports by Value", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ##################################### ##################################### # raw cotton chart volume #filtering data of fiscal year 2021-22 #df_yarn = df.loc[df['category'].isin(['Cotton Yarn'])] #calculating year-to-date YTD exports df_cotton['vol_YTD'] = df_cotton.groupby(['Fiscal Year'])['volume'].cumsum() df_cotton['pct_change_yoy_vol'] = df_cotton.groupby(['month'])['vol_YTD'].pct_change()*100 #filtering data of fiscal year 2020-21 df_cotton_2020_21 = df_cotton.loc[df_cotton['Fiscal Year'].isin(['2020-2021'])] df_cotton_2021_22 = df_cotton.loc[df_cotton['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_cotton_2020_21['month'], y=df_cotton_2020_21['vol_YTD'], name='Exports in 2020-21', text=df_cotton_2020_21['vol_YTD'], textposition='auto', texttemplate='%{text:,}', hovertemplate='Exports to date: %{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_cotton_2021_22['month'], y=df_cotton_2021_22['vol_YTD'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Exports in 2021-22', text=df_cotton_2021_22['vol_YTD'], textposition='bottom right', texttemplate="%{text:,}", line=dict(color='Green', width=4), hovertemplate='Exports to date: %{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_cotton_2021_22['month'], y=df_cotton_2021_22['pct_change_yoy_vol'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_cotton_2021_22['pct_change_yoy_vol'], textposition='middle right', texttemplate="%{text:.2s}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='Cumulative Exports (Metric Tons)', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Pakistan Raw Cotton Exports by Volume", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ##################################### ##################################### # cotton chart export price df_cotton['pct_change_yoy_price'] = df_cotton.groupby(['month'])['unit_price'].pct_change()*100 df_cotton_2020_21 = df_cotton.loc[df_cotton['Fiscal Year'].isin(['2020-2021'])] df_cotton_2021_22 = df_cotton.loc[df_cotton['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_cotton_2020_21['month'], y=df_cotton_2020_21['unit_price'], name='Price in 2020-21', text=df_cotton_2020_21['unit_price'], textposition='auto', texttemplate='$%{text:.2f}', hovertemplate='Exports price:$%{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_cotton_2021_22['month'], y=df_cotton_2021_22['unit_price'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Price in 2021-22', text=df_cotton_2021_22['unit_price'], textposition='bottom right', texttemplate="$%{text:.2f}", line=dict(color='Green', width=4), hovertemplate='Exports price:$%{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_cotton_2021_22['month'], y=df_cotton_2021_22['pct_change_yoy_price'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_cotton_2021_22['pct_change_yoy_price'], textposition='middle right', texttemplate="%{text:.2}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='US$ per Kg', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Pakistan Raw Cotton Average Export Price", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) #st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive elif page == 'Cotton Yarn Exports': ##################################### ##################################### # yarn chart US$ df = pd.read_csv('monthly_textile_exports_pbs.csv') df['date'] = pd.to_datetime(df['date'], infer_datetime_format=True) df['year'] = df['date'].dt.year #creates a year column out of datetime columns df['month'] = df['date'].dt.month #creates a month column out of datetime columns df['year'] = df['year'].astype('string') #converting year column into string for filtering df['month'] = df['month'].astype('string') #converting year column into string for filtering df['Fiscal Year'] = df['date'].dt.to_period('Q-JUN').dt.qyear.apply(lambda x: str(x-1) + "-" + str(x)) #adding month column df['month'] = df['date'].dt.strftime('%b') #creating month names column #filtering data of fiscal year 2021-22 df_yarn = df.loc[df['category'].isin(['Cotton Yarn'])] #calculating year-to-date YTD exports df_yarn['Exports_YTD'] = df_yarn.groupby(['Fiscal Year'])['Exports_US$'].cumsum() df_yarn['pct_change_yoy'] = df_yarn.groupby(['month'])['Exports_YTD'].pct_change()*100 #filtering data of fiscal year 2020-21 df_yarn_2020_21 = df_yarn.loc[df_yarn['Fiscal Year'].isin(['2020-2021'])] df_yarn_2021_22 = df_yarn.loc[df_yarn['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_yarn_2020_21['month'], y=df_yarn_2020_21['Exports_YTD'], name='Exports in 2020-21', text=df_yarn_2020_21['Exports_YTD'], textposition='auto', texttemplate='%{text:,}', hovertemplate='Exports to date: %{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_yarn_2021_22['month'], y=df_yarn_2021_22['Exports_YTD'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Exports in 2021-22', text=df_yarn_2021_22['Exports_YTD'], textposition='top center', texttemplate="%{text:,}", line=dict(color='Green', width=4), hovertemplate='Exports to date: %{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_yarn_2021_22['month'], y=df_yarn_2021_22['pct_change_yoy'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_yarn_2021_22['pct_change_yoy'], textposition='middle right', texttemplate="%{text:.2s}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='Cumulative Exports (US$ Billion)', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Pakistan Cotton Yarn Exports by Value", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ##################################### ##################################### # yarn chart volume #filtering data of fiscal year 2021-22 #df_yarn = df.loc[df['category'].isin(['Cotton Yarn'])] #calculating year-to-date YTD exports df_yarn['vol_YTD'] = df_yarn.groupby(['Fiscal Year'])['volume'].cumsum() df_yarn['pct_change_yoy_vol'] = df_yarn.groupby(['month'])['vol_YTD'].pct_change()*100 #filtering data of fiscal year 2020-21 df_yarn_2020_21 = df_yarn.loc[df_yarn['Fiscal Year'].isin(['2020-2021'])] df_yarn_2021_22 = df_yarn.loc[df_yarn['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_yarn_2020_21['month'], y=df_yarn_2020_21['vol_YTD'], name='Exports in 2020-21', text=df_yarn_2020_21['vol_YTD'], textposition='auto', texttemplate='%{text:,}', hovertemplate='Exports to date: %{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_yarn_2021_22['month'], y=df_yarn_2021_22['vol_YTD'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Exports in 2021-22', text=df_yarn_2021_22['vol_YTD'], textposition='top center', texttemplate="%{text:,}", line=dict(color='Green', width=4), hovertemplate='Exports to date: %{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_yarn_2021_22['month'], y=df_yarn_2021_22['pct_change_yoy_vol'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_yarn_2021_22['pct_change_yoy_vol'], textposition='middle right', texttemplate="%{text:.2s}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='Cumulative Exports (Metric Tons)', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Pakistan Cotton Yarn Exports by Volume", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ##################################### ##################################### # yarn chart export price df_yarn['pct_change_yoy_price'] = df_yarn.groupby(['month'])['unit_price'].pct_change()*100 df_yarn_2020_21 = df_yarn.loc[df_yarn['Fiscal Year'].isin(['2020-2021'])] df_yarn_2021_22 = df_yarn.loc[df_yarn['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_yarn_2020_21['month'], y=df_yarn_2020_21['unit_price'], name='Price in 2020-21', text=df_yarn_2020_21['unit_price'], textposition='auto', texttemplate='$%{text:.2f}', hovertemplate='Exports price:$%{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_yarn_2021_22['month'], y=df_yarn_2021_22['unit_price'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Price in 2021-22', text=df_yarn_2021_22['unit_price'], textposition='bottom right', texttemplate="$%{text:.2f}", line=dict(color='Green', width=4), hovertemplate='Exports price:$%{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_yarn_2021_22['month'], y=df_yarn_2021_22['pct_change_yoy_price'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_yarn_2021_22['pct_change_yoy_price'], textposition='middle right', texttemplate="%{text:.2s}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='US$ per Kg', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Pakistan Cotton Yarn Average Export Price", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive elif page == 'Cotton Cloth Exports': ##################################### ##################################### # cloth chart US$ df = pd.read_csv('monthly_textile_exports_pbs.csv') df['date'] = pd.to_datetime(df['date'], infer_datetime_format=True) df['year'] = df['date'].dt.year #creates a year column out of datetime columns df['month'] = df['date'].dt.month #creates a month column out of datetime columns df['year'] = df['year'].astype('string') #converting year column into string for filtering df['month'] = df['month'].astype('string') #converting year column into string for filtering df['Fiscal Year'] = df['date'].dt.to_period('Q-JUN').dt.qyear.apply(lambda x: str(x-1) + "-" + str(x)) #adding month column df['month'] = df['date'].dt.strftime('%b') #creating month names column #filtering data of fiscal year 2021-22 df_cloth = df.loc[df['category'].isin(['Cotton Cloth'])] #calculating year-to-date YTD exports df_cloth['Exports_YTD'] = df_cloth.groupby(['Fiscal Year'])['Exports_US$'].cumsum() df_cloth['pct_change_yoy'] = df_cloth.groupby(['month'])['Exports_YTD'].pct_change()*100 #filtering data of fiscal year 2020-21 df_cloth_2020_21 = df_cloth.loc[df_cloth['Fiscal Year'].isin(['2020-2021'])] df_cloth_2021_22 = df_cloth.loc[df_cloth['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_cloth_2020_21['month'], y=df_cloth_2020_21['Exports_YTD'], name='Exports in 2020-21', text=df_cloth_2020_21['Exports_YTD'], textposition='auto', texttemplate='%{text:,}', hovertemplate='Exports to date: %{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_cloth_2021_22['month'], y=df_cloth_2021_22['Exports_YTD'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Exports in 2021-22', text=df_cloth_2021_22['Exports_YTD'], textposition='top center', texttemplate="%{text:,}", line=dict(color='Green', width=4), hovertemplate='Exports to date: %{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_cloth_2021_22['month'], y=df_cloth_2021_22['pct_change_yoy'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_cloth_2021_22['pct_change_yoy'], textposition='middle right', texttemplate="%{text:.2s}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='Cumulative Exports (US$)', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Pakistan Cotton Cloth Exports by Value", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ##################################### ##################################### # cloth chart volume #filtering data of fiscal year 2021-22 #df_yarn = df.loc[df['category'].isin(['Cotton Yarn'])] #calculating year-to-date YTD exports df_cloth['vol_YTD'] = df_cloth.groupby(['Fiscal Year'])['volume'].cumsum() df_cloth['pct_change_yoy_vol'] = df_cloth.groupby(['month'])['vol_YTD'].pct_change()*100 #filtering data of fiscal year 2020-21 df_cloth_2020_21 = df_cloth.loc[df_cloth['Fiscal Year'].isin(['2020-2021'])] df_cloth_2021_22 = df_cloth.loc[df_cloth['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_cloth_2020_21['month'], y=df_cloth_2020_21['vol_YTD'], name='Exports in 2020-21', text=df_cloth_2020_21['vol_YTD'], textposition='auto', texttemplate='%{text:,}', hovertemplate='Exports to date: %{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_cloth_2021_22['month'], y=df_cloth_2021_22['vol_YTD'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Exports in 2021-22', text=df_cloth_2021_22['vol_YTD'], textposition='top center', texttemplate="%{text:,}", line=dict(color='Green', width=4), hovertemplate='Exports to date: %{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_cloth_2021_22['month'], y=df_cloth_2021_22['pct_change_yoy_vol'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_cloth_2021_22['pct_change_yoy_vol'], textposition='middle right', texttemplate="%{text:.2s}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='Cumulative Exports (Metric Tons)', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Pakistan Cotton Cloth Exports by Volume", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ##################################### ##################################### # cloth chart export price df_cloth['pct_change_yoy_price'] = df_cloth.groupby(['month'])['unit_price'].pct_change()*100 df_cloth_2020_21 = df_cloth.loc[df_cloth['Fiscal Year'].isin(['2020-2021'])] df_cloth_2021_22 = df_cloth.loc[df_cloth['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_cloth_2020_21['month'], y=df_cloth_2020_21['unit_price'], name='Price in 2020-21', text=df_cloth_2020_21['unit_price'], textposition='auto', texttemplate='$%{text:.2f}', hovertemplate='Exports price:$%{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_cloth_2021_22['month'], y=df_cloth_2021_22['unit_price'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Price in 2021-22', text=df_cloth_2021_22['unit_price'], textposition='bottom right', texttemplate="$%{text:.2f}", line=dict(color='Green', width=4), hovertemplate='Exports price:$%{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_cloth_2021_22['month'], y=df_cloth_2021_22['pct_change_yoy_price'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_cloth_2021_22['pct_change_yoy_price'], textposition='middle right', texttemplate="%{text:.2s}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='US$ per Kg', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Pakistan Cotton Cloth Average Export Price", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ##################################### elif page == 'Readymade Garments Exports': ##################################### ##################################### # garment chart value #importing csv file as dataframe df = pd.read_csv('monthly_textile_exports_pbs.csv') df['date'] = pd.to_datetime(df['date'], infer_datetime_format=True) df['year'] = df['date'].dt.year #creates a year column out of datetime columns df['month'] = df['date'].dt.month #creates a month column out of datetime columns df['year'] = df['year'].astype('string') #converting year column into string for filtering df['month'] = df['month'].astype('string') #converting year column into string for filtering df['Fiscal Year'] = df['date'].dt.to_period('Q-JUN').dt.qyear.apply(lambda x: str(x-1) + "-" + str(x)) #adding month column df['month'] = df['date'].dt.strftime('%b') #creating month names column df_garment = df.loc[df['category'].isin(['Garments'])] ################################## ################################## #calculating year-to-date YTD exports df_garment['Exports_YTD'] = df_garment.groupby(['Fiscal Year'])['Exports_US$'].cumsum() df_garment['pct_change_yoy'] = df_garment.groupby(['month'])['Exports_YTD'].pct_change()*100 #filtering data of fiscal year 2020-21 df_garment_2020_21 = df_garment.loc[df_garment['Fiscal Year'].isin(['2020-2021'])] df_garment_2021_22 = df_garment.loc[df_garment['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_garment_2020_21['month'], y=df_garment_2020_21['Exports_YTD'], name='Exports in 2020-21', text=df_garment_2020_21['Exports_YTD'], textposition='auto', texttemplate='%{text:,}', hovertemplate='Exports to date: %{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_garment_2021_22['month'], y=df_garment_2021_22['Exports_YTD'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Exports in 2021-22', text=df_garment_2021_22['Exports_YTD'], textposition='top center', texttemplate="%{text:,}", line=dict(color='Green', width=4), hovertemplate='Exports to date: %{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_garment_2021_22['month'], y=df_garment_2021_22['pct_change_yoy'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_garment_2021_22['pct_change_yoy'], textposition='middle right', texttemplate="%{text:.2s}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") from PIL import Image image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='Cumulative Exports (US$ Billion)', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Pakistan Garment Exports by Value", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ################################## #calculating year-to-date YTD exports df_garment['Exports_YTD_vol'] = df_garment.groupby(['Fiscal Year'])['volume'].cumsum() df_garment['pct_change_yoy_vol'] = df_garment.groupby(['month'])['Exports_YTD_vol'].pct_change()*100 #filtering data of fiscal year 2020-21 df_garment_2020_21 = df_garment.loc[df_garment['Fiscal Year'].isin(['2020-2021'])] df_garment_2021_22 = df_garment.loc[df_garment['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_garment_2020_21['month'], y=df_garment_2020_21['Exports_YTD_vol'], name='Exports in 2020-21', text=df_garment_2020_21['Exports_YTD_vol'], textposition='auto', texttemplate='%{text:,}', hovertemplate='Exports to date: %{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_garment_2021_22['month'], y=df_garment_2021_22['Exports_YTD_vol'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Exports in 2021-22', text=df_garment_2021_22['Exports_YTD_vol'], textposition='top center', texttemplate="%{text:,}", line=dict(color='Green', width=4), hovertemplate='Exports to date: %{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_garment_2021_22['month'], y=df_garment_2021_22['pct_change_yoy_vol'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_garment_2021_22['pct_change_yoy_vol'], textposition='middle right', texttemplate="%{text:.2s}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='Cumulative Exports (Dozens)', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Pakistan Garments Exports by Volume", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ##################################### # garment chart export price df_garment['pct_change_yoy_price'] = df_garment.groupby(['month'])['unit_price'].pct_change()*100 df_garment_2020_21 = df_garment.loc[df_garment['Fiscal Year'].isin(['2020-2021'])] df_garment_2021_22 = df_garment.loc[df_garment['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_garment_2020_21['month'], y=df_garment_2020_21['unit_price'], name='Price in 2020-21', text=df_garment_2020_21['unit_price'], textposition='auto', texttemplate='$%{text:.2f}', hovertemplate='Exports price:$%{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_garment_2021_22['month'], y=df_garment_2021_22['unit_price'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Price in 2021-22', text=df_garment_2021_22['unit_price'], textposition='bottom right', texttemplate="$%{text:.2f}", line=dict(color='Green', width=4), hovertemplate='Exports price:$%{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_garment_2021_22['month'], y=df_garment_2021_22['pct_change_yoy_price'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_garment_2021_22['pct_change_yoy_price'], textposition='middle right', texttemplate="%{text:.2s}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='US$ per Dozen', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Pakistan Garments Average Export Price", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ##################################### elif page == 'Knitwear Exports': ##################################### ##################################### #importing csv file as dataframe df = pd.read_csv('monthly_textile_exports_pbs.csv') df['date'] = pd.to_datetime(df['date'], infer_datetime_format=True) df['year'] = df['date'].dt.year #creates a year column out of datetime columns df['month'] = df['date'].dt.month #creates a month column out of datetime columns df['year'] = df['year'].astype('string') #converting year column into string for filtering df['month'] = df['month'].astype('string') #converting year column into string for filtering df['Fiscal Year'] = df['date'].dt.to_period('Q-JUN').dt.qyear.apply(lambda x: str(x-1) + "-" + str(x)) #adding month column df['month'] = df['date'].dt.strftime('%b') #creating month names column # knitwear chart value df_knitwear = df.loc[df['category'].isin(['Knitwear'])] #calculating year-to-date YTD exports df_knitwear['Exports_YTD'] = df_knitwear.groupby(['Fiscal Year'])['Exports_US$'].cumsum() df_knitwear['pct_change_yoy'] = df_knitwear.groupby(['month'])['Exports_YTD'].pct_change()*100 #filtering data of fiscal year 2020-21 df_knitwear_2020_21 = df_knitwear.loc[df_knitwear['Fiscal Year'].isin(['2020-2021'])] df_knitwear_2021_22 = df_knitwear.loc[df_knitwear['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_knitwear_2020_21['month'], y=df_knitwear_2020_21['Exports_YTD'], name='Exports in 2020-21', text=df_knitwear_2020_21['Exports_YTD'], textposition='auto', texttemplate='%{text:,}', hovertemplate='Exports to date: %{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_knitwear_2021_22['month'], y=df_knitwear_2021_22['Exports_YTD'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Exports in 2021-22', text=df_knitwear_2021_22['Exports_YTD'], textposition='top center', texttemplate="%{text:,}", line=dict(color='Green', width=4), hovertemplate='Exports to date: %{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_knitwear_2021_22['month'], y=df_knitwear_2021_22['pct_change_yoy'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_knitwear_2021_22['pct_change_yoy'], textposition='middle right', texttemplate="%{text:.2s}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") from PIL import Image image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='Cumulative Exports (US$ Billion)', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Pakistan Knitwear Exports by Value", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ############################################### ############################################# #calculating year-to-date YTD exports by volume df_knitwear['Exports_YTD_vol'] = df_knitwear.groupby(['Fiscal Year'])['volume'].cumsum() df_knitwear['pct_change_yoy_vol'] = df_knitwear.groupby(['month'])['Exports_YTD_vol'].pct_change()*100 #filtering data of fiscal year 2020-21 df_knitwear_2020_21 = df_knitwear.loc[df_knitwear['Fiscal Year'].isin(['2020-2021'])] df_knitwear_2021_22 = df_knitwear.loc[df_knitwear['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_knitwear_2020_21['month'], y=df_knitwear_2020_21['Exports_YTD_vol'], name='Exports in 2020-21', text=df_knitwear_2020_21['Exports_YTD_vol'], textposition='auto', texttemplate='%{text:,}', hovertemplate='Exports to date: %{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_knitwear_2021_22['month'], y=df_knitwear_2021_22['Exports_YTD_vol'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Exports in 2021-22', text=df_knitwear_2021_22['Exports_YTD_vol'], textposition='top center', texttemplate="%{text:,}", line=dict(color='Green', width=4), hovertemplate='Exports to date: %{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_knitwear_2021_22['month'], y=df_knitwear_2021_22['pct_change_yoy_vol'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_knitwear_2021_22['pct_change_yoy_vol'], textposition='middle right', texttemplate="%{text:.2f}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='Cumulative Exports (Dozens)', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Pakistan Knitwear Exports by Volume", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ##################################### # garment chart export price df_knitwear['pct_change_yoy_price'] = df_knitwear.groupby(['month'])['unit_price'].pct_change()*100 df_knitwear_2020_21 = df_knitwear.loc[df_knitwear['Fiscal Year'].isin(['2020-2021'])] df_knitwear_2021_22 = df_knitwear.loc[df_knitwear['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_knitwear_2020_21['month'], y=df_knitwear_2020_21['unit_price'], name='Price in 2020-21', text=df_knitwear_2020_21['unit_price'], textposition='auto', texttemplate='$%{text:.2f}', hovertemplate='Exports price:$%{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_knitwear_2021_22['month'], y=df_knitwear_2021_22['unit_price'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Price in 2021-22', text=df_knitwear_2021_22['unit_price'], textposition='bottom right', texttemplate="$%{text:.2f}", line=dict(color='Green', width=4), hovertemplate='Exports price:$%{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_knitwear_2021_22['month'], y=df_knitwear_2021_22['pct_change_yoy_price'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_knitwear_2021_22['pct_change_yoy_price'], textposition='middle right', texttemplate="%{text:.2s}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='US$ per Dozen', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Pakistan Knitwear Average Export Price", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ##################################### ################# elif page == 'Artifical Silk & Synthetics Exports': ##################################### ##################################### #importing csv file as dataframe df = pd.read_csv('monthly_textile_exports_pbs.csv') df['date'] = pd.to_datetime(df['date'], infer_datetime_format=True) df['year'] = df['date'].dt.year #creates a year column out of datetime columns df['month'] = df['date'].dt.month #creates a month column out of datetime columns df['year'] = df['year'].astype('string') #converting year column into string for filtering df['month'] = df['month'].astype('string') #converting year column into string for filtering df['Fiscal Year'] = df['date'].dt.to_period('Q-JUN').dt.qyear.apply(lambda x: str(x-1) + "-" + str(x)) #adding month column df['month'] = df['date'].dt.strftime('%b') #creating month names column # knitwear chart value df_s = df.loc[df['category'].isin(['Artificial Silk & Synthetics'])] #calculating year-to-date YTD exports df_s['Exports_YTD'] = df_s.groupby(['Fiscal Year'])['Exports_US$'].cumsum() df_s['pct_change_yoy'] = df_s.groupby(['month'])['Exports_YTD'].pct_change()*100 #filtering data of fiscal year 2020-21 df_s_2020_21 = df_s.loc[df_s['Fiscal Year'].isin(['2020-2021'])] df_s_2021_22 = df_s.loc[df_s['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_s_2020_21['month'], y=df_s_2020_21['Exports_YTD'], name='Exports in 2020-21', text=df_s_2020_21['Exports_YTD'], textposition='auto', texttemplate='%{text:,}', hovertemplate='Exports to date: %{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_s_2021_22['month'], y=df_s_2021_22['Exports_YTD'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Exports in 2021-22', text=df_s_2021_22['Exports_YTD'], textposition='top center', texttemplate="%{text:,}", line=dict(color='Green', width=4), hovertemplate='Exports to date: %{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_s_2021_22['month'], y=df_s_2021_22['pct_change_yoy'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_s_2021_22['pct_change_yoy'], textposition='middle right', texttemplate="%{text:.2s}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") from PIL import Image image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='Cumulative Exports (US$ Billion)', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Art. Silk & Sythetics Exports by Value", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ############################################### ############################################# #calculating year-to-date YTD exports by volume df_s['Exports_YTD_vol'] = df_s.groupby(['Fiscal Year'])['volume'].cumsum() df_s['pct_change_yoy_vol'] = df_s.groupby(['month'])['Exports_YTD_vol'].pct_change()*100 #filtering data of fiscal year 2020-21 df_s_2020_21 = df_s.loc[df_s['Fiscal Year'].isin(['2020-2021'])] df_s_2021_22 = df_s.loc[df_s['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_s_2020_21['month'], y=df_s_2020_21['Exports_YTD_vol'], name='Exports in 2020-21', text=df_s_2020_21['Exports_YTD_vol'], textposition='auto', texttemplate='%{text:,}', hovertemplate='Exports to date: %{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_s_2021_22['month'], y=df_s_2021_22['Exports_YTD_vol'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Exports in 2021-22', text=df_s_2021_22['Exports_YTD_vol'], textposition='top center', texttemplate="%{text:,}", line=dict(color='Green', width=4), hovertemplate='Exports to date: %{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_s_2021_22['month'], y=df_s_2021_22['pct_change_yoy_vol'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_s_2021_22['pct_change_yoy_vol'], textposition='middle right', texttemplate="%{text:.2f}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='Cumulative Exports (Metric Tons)', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Art. Silk & Synthetics Exports by Volume", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ##################################### # tents yarn chart export price df_s['pct_change_yoy_price'] = df_s.groupby(['month'])['unit_price'].pct_change()*100 df_s_2020_21 = df_s.loc[df_s['Fiscal Year'].isin(['2020-2021'])] df_s_2021_22 = df_s.loc[df_s['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_s_2020_21['month'], y=df_s_2020_21['unit_price'], name='Price in 2020-21', text=df_s_2020_21['unit_price'], textposition='auto', texttemplate='$%{text:.2f}', hovertemplate='Exports price:$%{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_s_2021_22['month'], y=df_s_2021_22['unit_price'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Price in 2021-22', text=df_s_2021_22['unit_price'], textposition='bottom right', texttemplate="$%{text:.2f}", line=dict(color='Green', width=4), hovertemplate='Exports price:$%{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_s_2021_22['month'], y=df_s_2021_22['pct_change_yoy_price'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_s_2021_22['pct_change_yoy_price'], textposition='middle right', texttemplate="%{text:.2s}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='US$ per Kg', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Pakistan Art. Silk & Synthetics Average Export Price", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ################# ################# elif page == 'Other Textiles Exports': ##################################### ##################################### #importing csv file as dataframe df = pd.read_csv('monthly_textile_exports_pbs.csv') df['date'] = pd.to_datetime(df['date'], infer_datetime_format=True) df['year'] = df['date'].dt.year #creates a year column out of datetime columns df['month'] = df['date'].dt.month #creates a month column out of datetime columns df['year'] = df['year'].astype('string') #converting year column into string for filtering df['month'] = df['month'].astype('string') #converting year column into string for filtering df['Fiscal Year'] = df['date'].dt.to_period('Q-JUN').dt.qyear.apply(lambda x: str(x-1) + "-" + str(x)) #adding month column df['month'] = df['date'].dt.strftime('%b') #creating month names column # knitwear chart value df_o = df.loc[df['category'].isin(['Other Textiles'])] #calculating year-to-date YTD exports df_o['Exports_YTD'] = df_o.groupby(['Fiscal Year'])['Exports_US$'].cumsum() df_o['pct_change_yoy'] = df_o.groupby(['month'])['Exports_YTD'].pct_change()*100 #filtering data of fiscal year 2020-21 df_o_2020_21 = df_o.loc[df_o['Fiscal Year'].isin(['2020-2021'])] df_o_2021_22 = df_o.loc[df_o['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_o_2020_21['month'], y=df_o_2020_21['Exports_YTD'], name='Exports in 2020-21', text=df_o_2020_21['Exports_YTD'], textposition='auto', texttemplate='%{text:,}', hovertemplate='Exports to date: %{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_o_2021_22['month'], y=df_o_2021_22['Exports_YTD'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Exports in 2021-22', text=df_o_2021_22['Exports_YTD'], textposition='top center', texttemplate="%{text:,}", line=dict(color='Green', width=4), hovertemplate='Exports to date: %{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_o_2021_22['month'], y=df_o_2021_22['pct_change_yoy'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_o_2021_22['pct_change_yoy'], textposition='middle right', texttemplate="%{text:.2s}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") from PIL import Image image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='Cumulative Exports (US$ Billion)', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Other Textiles Exports by Value", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ############################################### ################# ################# elif page == 'Made-ups excluding Bedwear & Towels': ##################################### ##################################### #importing csv file as dataframe df = pd.read_csv('monthly_textile_exports_pbs.csv') df['date'] = pd.to_datetime(df['date'], infer_datetime_format=True) df['year'] = df['date'].dt.year #creates a year column out of datetime columns df['month'] = df['date'].dt.month #creates a month column out of datetime columns df['year'] = df['year'].astype('string') #converting year column into string for filtering df['month'] = df['month'].astype('string') #converting year column into string for filtering df['Fiscal Year'] = df['date'].dt.to_period('Q-JUN').dt.qyear.apply(lambda x: str(x-1) + "-" + str(x)) #adding month column df['month'] = df['date'].dt.strftime('%b') #creating month names column # knitwear chart value df_m = df.loc[df['category'].isin(['Madeups'])] #calculating year-to-date YTD exports df_m['Exports_YTD'] = df_m.groupby(['Fiscal Year'])['Exports_US$'].cumsum() df_m['pct_change_yoy'] = df_m.groupby(['month'])['Exports_YTD'].pct_change()*100 #filtering data of fiscal year 2020-21 df_m_2020_21 = df_m.loc[df_m['Fiscal Year'].isin(['2020-2021'])] df_m_2021_22 = df_m.loc[df_m['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_m_2020_21['month'], y=df_m_2020_21['Exports_YTD'], name='Exports in 2020-21', text=df_m_2020_21['Exports_YTD'], textposition='auto', texttemplate='%{text:,}', hovertemplate='Exports to date: %{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_m_2021_22['month'], y=df_m_2021_22['Exports_YTD'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Exports in 2021-22', text=df_m_2021_22['Exports_YTD'], textposition='top center', texttemplate="%{text:,}", line=dict(color='Green', width=4), hovertemplate='Exports to date: %{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_m_2021_22['month'], y=df_m_2021_22['pct_change_yoy'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_m_2021_22['pct_change_yoy'], textposition='middle right', texttemplate="%{text:.2s}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") from PIL import Image image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='Cumulative Exports (US$ Billion)', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Madeups Exports by Value", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ############################################### ############################################# #calculating year-to-date YTD exports by volume df_m['Exports_YTD_vol'] = df_m.groupby(['Fiscal Year'])['volume'].cumsum() df_m['pct_change_yoy_vol'] = df_m.groupby(['month'])['Exports_YTD_vol'].pct_change()*100 #filtering data of fiscal year 2020-21 df_m_2020_21 = df_m.loc[df_m['Fiscal Year'].isin(['2020-2021'])] df_m_2021_22 = df_m.loc[df_m['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_m_2020_21['month'], y=df_m_2020_21['Exports_YTD_vol'], name='Exports in 2020-21', text=df_m_2020_21['Exports_YTD_vol'], textposition='auto', texttemplate='%{text:,}', hovertemplate='Exports to date: %{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_m_2021_22['month'], y=df_m_2021_22['Exports_YTD_vol'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Exports in 2021-22', text=df_m_2021_22['Exports_YTD_vol'], textposition='top center', texttemplate="%{text:,}", line=dict(color='Green', width=4), hovertemplate='Exports to date: %{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_m_2021_22['month'], y=df_m_2021_22['pct_change_yoy_vol'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_m_2021_22['pct_change_yoy_vol'], textposition='middle right', texttemplate="%{text:.2f}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='Cumulative Exports (Metric Tons)', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Madeup Exports by Volume", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) #st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ################# elif page == 'Tents & Tarpaulines Exports': ##################################### ##################################### #importing csv file as dataframe df = pd.read_csv('monthly_textile_exports_pbs.csv') df['date'] = pd.to_datetime(df['date'], infer_datetime_format=True) df['year'] = df['date'].dt.year #creates a year column out of datetime columns df['month'] = df['date'].dt.month #creates a month column out of datetime columns df['year'] = df['year'].astype('string') #converting year column into string for filtering df['month'] = df['month'].astype('string') #converting year column into string for filtering df['Fiscal Year'] = df['date'].dt.to_period('Q-JUN').dt.qyear.apply(lambda x: str(x-1) + "-" + str(x)) #adding month column df['month'] = df['date'].dt.strftime('%b') #creating month names column # knitwear chart value df_tents = df.loc[df['category'].isin(['Tents, Tarpaulines'])] #calculating year-to-date YTD exports df_tents['Exports_YTD'] = df_tents.groupby(['Fiscal Year'])['Exports_US$'].cumsum() df_tents['pct_change_yoy'] = df_tents.groupby(['month'])['Exports_YTD'].pct_change()*100 #filtering data of fiscal year 2020-21 df_tents_2020_21 = df_tents.loc[df_tents['Fiscal Year'].isin(['2020-2021'])] df_tents_2021_22 = df_tents.loc[df_tents['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_tents_2020_21['month'], y=df_tents_2020_21['Exports_YTD'], name='Exports in 2020-21', text=df_tents_2020_21['Exports_YTD'], textposition='auto', texttemplate='%{text:,}', hovertemplate='Exports to date: %{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_tents_2021_22['month'], y=df_tents_2021_22['Exports_YTD'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Exports in 2021-22', text=df_tents_2021_22['Exports_YTD'], textposition='top center', texttemplate="%{text:,}", line=dict(color='Green', width=4), hovertemplate='Exports to date: %{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_tents_2021_22['month'], y=df_tents_2021_22['pct_change_yoy'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_tents_2021_22['pct_change_yoy'], textposition='middle right', texttemplate="%{text:.2s}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") from PIL import Image image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='Cumulative Exports (US$ Billion)', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Tents & Tarpaulines Exports by Value", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ############################################### ############################################# #calculating year-to-date YTD exports by volume df_tents['Exports_YTD_vol'] = df_tents.groupby(['Fiscal Year'])['volume'].cumsum() df_tents['pct_change_yoy_vol'] = df_tents.groupby(['month'])['Exports_YTD_vol'].pct_change()*100 #filtering data of fiscal year 2020-21 df_tents_2020_21 = df_tents.loc[df_tents['Fiscal Year'].isin(['2020-2021'])] df_tents_2021_22 = df_tents.loc[df_tents['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_tents_2020_21['month'], y=df_tents_2020_21['Exports_YTD_vol'], name='Exports in 2020-21', text=df_tents_2020_21['Exports_YTD_vol'], textposition='auto', texttemplate='%{text:,}', hovertemplate='Exports to date: %{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_tents_2021_22['month'], y=df_tents_2021_22['Exports_YTD_vol'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Exports in 2021-22', text=df_tents_2021_22['Exports_YTD_vol'], textposition='top center', texttemplate="%{text:,}", line=dict(color='Green', width=4), hovertemplate='Exports to date: %{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_tents_2021_22['month'], y=df_tents_2021_22['pct_change_yoy_vol'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_tents_2021_22['pct_change_yoy_vol'], textposition='middle right', texttemplate="%{text:.2f}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='Cumulative Exports (Metric Tons)', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Tents & Tarpaulines Exports by Volume", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ##################################### # tents yarn chart export price df_tents['pct_change_yoy_price'] = df_tents.groupby(['month'])['unit_price'].pct_change()*100 df_tents_2020_21 = df_tents.loc[df_tents['Fiscal Year'].isin(['2020-2021'])] df_tents_2021_22 = df_tents.loc[df_tents['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_tents_2020_21['month'], y=df_tents_2020_21['unit_price'], name='Price in 2020-21', text=df_tents_2020_21['unit_price'], textposition='auto', texttemplate='$%{text:.2f}', hovertemplate='Exports price:$%{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_tents_2021_22['month'], y=df_tents_2021_22['unit_price'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Price in 2021-22', text=df_tents_2021_22['unit_price'], textposition='bottom right', texttemplate="$%{text:.2f}", line=dict(color='Green', width=4), hovertemplate='Exports price:$%{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_tents_2021_22['month'], y=df_tents_2021_22['pct_change_yoy_price'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_tents_2021_22['pct_change_yoy_price'], textposition='middle right', texttemplate="%{text:.2s}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='US$ per Kg', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Pakistan Tents & Tarpaulines Average Export Price", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ################### elif page == 'Non-Cotton Yarn Exports': ##################################### ##################################### #importing csv file as dataframe df = pd.read_csv('monthly_textile_exports_pbs.csv') df['date'] = pd.to_datetime(df['date'], infer_datetime_format=True) df['year'] = df['date'].dt.year #creates a year column out of datetime columns df['month'] = df['date'].dt.month #creates a month column out of datetime columns df['year'] = df['year'].astype('string') #converting year column into string for filtering df['month'] = df['month'].astype('string') #converting year column into string for filtering df['Fiscal Year'] = df['date'].dt.to_period('Q-JUN').dt.qyear.apply(lambda x: str(x-1) + "-" + str(x)) #adding month column df['month'] = df['date'].dt.strftime('%b') #creating month names column # knitwear chart value df_ncyarn = df.loc[df['category'].isin(['Non-Cotton Yarn'])] #calculating year-to-date YTD exports df_ncyarn['Exports_YTD'] = df_ncyarn.groupby(['Fiscal Year'])['Exports_US$'].cumsum() df_ncyarn['pct_change_yoy'] = df_ncyarn.groupby(['month'])['Exports_YTD'].pct_change()*100 #filtering data of fiscal year 2020-21 df_ncyarn_2020_21 = df_ncyarn.loc[df_ncyarn['Fiscal Year'].isin(['2020-2021'])] df_ncyarn_2021_22 = df_ncyarn.loc[df_ncyarn['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_ncyarn_2020_21['month'], y=df_ncyarn_2020_21['Exports_YTD'], name='Exports in 2020-21', text=df_ncyarn_2020_21['Exports_YTD'], textposition='auto', texttemplate='%{text:,}', hovertemplate='Exports to date: %{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_ncyarn_2021_22['month'], y=df_ncyarn_2021_22['Exports_YTD'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Exports in 2021-22', text=df_ncyarn_2021_22['Exports_YTD'], textposition='top center', texttemplate="%{text:,}", line=dict(color='Green', width=4), hovertemplate='Exports to date: %{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_ncyarn_2021_22['month'], y=df_ncyarn_2021_22['pct_change_yoy'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_ncyarn_2021_22['pct_change_yoy'], textposition='middle right', texttemplate="%{text:.2s}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") from PIL import Image image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='Cumulative Exports (US$ Billion)', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Non-Cotton Yarn Exports by Value", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ############################################### ############################################# #calculating year-to-date YTD exports by volume df_ncyarn['Exports_YTD_vol'] = df_ncyarn.groupby(['Fiscal Year'])['volume'].cumsum() df_ncyarn['pct_change_yoy_vol'] = df_ncyarn.groupby(['month'])['Exports_YTD_vol'].pct_change()*100 #filtering data of fiscal year 2020-21 df_ncyarn_2020_21 = df_ncyarn.loc[df_ncyarn['Fiscal Year'].isin(['2020-2021'])] df_ncyarn_2021_22 = df_ncyarn.loc[df_ncyarn['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_ncyarn_2020_21['month'], y=df_ncyarn_2020_21['Exports_YTD_vol'], name='Exports in 2020-21', text=df_ncyarn_2020_21['Exports_YTD_vol'], textposition='auto', texttemplate='%{text:,}', hovertemplate='Exports to date: %{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_ncyarn_2021_22['month'], y=df_ncyarn_2021_22['Exports_YTD_vol'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Exports in 2021-22', text=df_ncyarn_2021_22['Exports_YTD_vol'], textposition='top center', texttemplate="%{text:,}", line=dict(color='Green', width=4), hovertemplate='Exports to date: %{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_ncyarn_2021_22['month'], y=df_ncyarn_2021_22['pct_change_yoy_vol'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_ncyarn_2021_22['pct_change_yoy_vol'], textposition='middle right', texttemplate="%{text:.2f}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='Cumulative Exports (Metric Tons)', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Non-Cotton Exports by Volume", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ##################################### # non-cotton yarn chart export price df_ncyarn['pct_change_yoy_price'] = df_ncyarn.groupby(['month'])['unit_price'].pct_change()*100 df_ncyarn_2020_21 = df_ncyarn.loc[df_ncyarn['Fiscal Year'].isin(['2020-2021'])] df_ncyarn_2021_22 = df_ncyarn.loc[df_ncyarn['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_ncyarn_2020_21['month'], y=df_ncyarn_2020_21['unit_price'], name='Price in 2020-21', text=df_ncyarn_2020_21['unit_price'], textposition='auto', texttemplate='$%{text:.2f}', hovertemplate='Exports price:$%{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_ncyarn_2021_22['month'], y=df_ncyarn_2021_22['unit_price'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Price in 2021-22', text=df_ncyarn_2021_22['unit_price'], textposition='bottom right', texttemplate="$%{text:.2f}", line=dict(color='Green', width=4), hovertemplate='Exports price:$%{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_ncyarn_2021_22['month'], y=df_ncyarn_2021_22['pct_change_yoy_price'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_ncyarn_2021_22['pct_change_yoy_price'], textposition='middle right', texttemplate="%{text:.2s}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='US$ per Kg', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Pakistan Non-Cotton Yarn Average Export Price", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ################ elif page == 'Bedwear Exports': ##################################### ##################################### #importing csv file as dataframe df = pd.read_csv('monthly_textile_exports_pbs.csv') df['date'] = pd.to_datetime(df['date'], infer_datetime_format=True) df['year'] = df['date'].dt.year #creates a year column out of datetime columns df['month'] = df['date'].dt.month #creates a month column out of datetime columns df['year'] = df['year'].astype('string') #converting year column into string for filtering df['month'] = df['month'].astype('string') #converting year column into string for filtering df['Fiscal Year'] = df['date'].dt.to_period('Q-JUN').dt.qyear.apply(lambda x: str(x-1) + "-" + str(x)) #adding month column df['month'] = df['date'].dt.strftime('%b') #creating month names column ##################################### # bedwear chart value df_bedwear = df.loc[df['category'].isin(['Bedwear'])] #calculating year-to-date YTD exports df_bedwear['Exports_YTD'] = df_bedwear.groupby(['Fiscal Year'])['Exports_US$'].cumsum() df_bedwear['pct_change_yoy'] = df_bedwear.groupby(['month'])['Exports_YTD'].pct_change()*100 #filtering data of fiscal year 2020-21 df_bedwear_2020_21 = df_bedwear.loc[df_bedwear['Fiscal Year'].isin(['2020-2021'])] df_bedwear_2021_22 = df_bedwear.loc[df_bedwear['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_bedwear_2020_21['month'], y=df_bedwear_2020_21['Exports_YTD'], name='Exports in 2020-21', text=df_bedwear_2020_21['Exports_YTD'], textposition='auto', texttemplate='%{text:,}', hovertemplate='Exports to date: %{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_bedwear_2021_22['month'], y=df_bedwear_2021_22['Exports_YTD'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Exports in 2021-22', text=df_bedwear_2021_22['Exports_YTD'], textposition='top center', texttemplate="%{text:,}", line=dict(color='Green', width=4), hovertemplate='Exports to date: %{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_bedwear_2021_22['month'], y=df_bedwear_2021_22['pct_change_yoy'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_bedwear_2021_22['pct_change_yoy'], textposition='middle right', texttemplate="%{text:.2s}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='Cumulative Exports (US$ Billion)', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Pakistan Bedwear Exports by Value", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ##################################### ##################################### # bedwear chart volume df_bedwear = df.loc[df['category'].isin(['Bedwear'])] #calculating year-to-date YTD exports df_bedwear['Exports_YTD_vol'] = df_bedwear.groupby(['Fiscal Year'])['volume'].cumsum() df_bedwear['pct_change_yoy_vol'] = df_bedwear.groupby(['month'])['Exports_YTD_vol'].pct_change()*100 #filtering data of fiscal year 2020-21 df_bedwear_2020_21 = df_bedwear.loc[df_bedwear['Fiscal Year'].isin(['2020-2021'])] df_bedwear_2021_22 = df_bedwear.loc[df_bedwear['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_bedwear_2020_21['month'], y=df_bedwear_2020_21['Exports_YTD_vol'], name='Exports in 2020-21', text=df_bedwear_2020_21['Exports_YTD_vol'], textposition='auto', texttemplate='%{text:,}', hovertemplate='Exports to date: %{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_bedwear_2021_22['month'], y=df_bedwear_2021_22['Exports_YTD_vol'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Exports in 2021-22', text=df_bedwear_2021_22['Exports_YTD_vol'], textposition='top center', texttemplate="%{text:,}", line=dict(color='Green', width=4), hovertemplate='Exports to date: %{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_bedwear_2021_22['month'], y=df_bedwear_2021_22['pct_change_yoy_vol'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_bedwear_2021_22['pct_change_yoy_vol'], textposition='middle right', texttemplate="%{text:.2f}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='Cumulative Exports (Metric Tons)', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Pakistan Bedwear Exports by Volume", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ##################################### # garment chart export price df_bedwear['pct_change_yoy_price'] = df_bedwear.groupby(['month'])['unit_price'].pct_change()*100 df_bedwear_2020_21 = df_bedwear.loc[df_bedwear['Fiscal Year'].isin(['2020-2021'])] df_bedwear_2021_22 = df_bedwear.loc[df_bedwear['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_bedwear_2020_21['month'], y=df_bedwear_2020_21['unit_price'], name='Price in 2020-21', text=df_bedwear_2020_21['unit_price'], textposition='auto', texttemplate='$%{text:.2f}', hovertemplate='Exports price:$%{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_bedwear_2021_22['month'], y=df_bedwear_2021_22['unit_price'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Price in 2021-22', text=df_bedwear_2021_22['unit_price'], textposition='bottom right', texttemplate="$%{text:.2f}", line=dict(color='Green', width=4), hovertemplate='Exports price:$%{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_bedwear_2021_22['month'], y=df_bedwear_2021_22['pct_change_yoy_price'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_bedwear_2021_22['pct_change_yoy_price'], textposition='middle right', texttemplate="%{text:.2s}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='US$ per Kg', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Pakistan Bedwear Average Export Price", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ##################################### ################ elif page == 'Towel Exports': ##################################### ##################################### #importing csv file as dataframe df = pd.read_csv('monthly_textile_exports_pbs.csv') df['date'] = pd.to_datetime(df['date'], infer_datetime_format=True) df['year'] = df['date'].dt.year #creates a year column out of datetime columns df['month'] = df['date'].dt.month #creates a month column out of datetime columns df['year'] = df['year'].astype('string') #converting year column into string for filtering df['month'] = df['month'].astype('string') #converting year column into string for filtering df['Fiscal Year'] = df['date'].dt.to_period('Q-JUN').dt.qyear.apply(lambda x: str(x-1) + "-" + str(x)) #adding month column df['month'] = df['date'].dt.strftime('%b') #creating month names column ##################################### # bedwear chart value df_towels = df.loc[df['category'].isin(['Towels'])] #calculating year-to-date YTD exports df_towels['Exports_YTD'] = df_towels.groupby(['Fiscal Year'])['Exports_US$'].cumsum() df_towels['pct_change_yoy'] = df_towels.groupby(['month'])['Exports_YTD'].pct_change()*100 #filtering data of fiscal year 2020-21 df_towels_2020_21 = df_towels.loc[df_towels['Fiscal Year'].isin(['2020-2021'])] df_towels_2021_22 = df_towels.loc[df_towels['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_towels_2020_21['month'], y=df_towels_2020_21['Exports_YTD'], name='Exports in 2020-21', text=df_towels_2020_21['Exports_YTD'], textposition='auto', texttemplate='%{text:,}', hovertemplate='Exports to date: %{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_towels_2021_22['month'], y=df_towels_2021_22['Exports_YTD'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Exports in 2021-22', text=df_towels_2021_22['Exports_YTD'], textposition='top center', texttemplate="%{text:,}", line=dict(color='Green', width=4), hovertemplate='Exports to date: %{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_towels_2021_22['month'], y=df_towels_2021_22['pct_change_yoy'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_towels_2021_22['pct_change_yoy'], textposition='middle right', texttemplate="%{text:.2s}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='Cumulative Exports (US$)', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Pakistan Towels Exports by Value", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ##################################### ##################################### # bedwear chart volume #calculating year-to-date YTD exports df_towels['Exports_YTD_vol'] = df_towels.groupby(['Fiscal Year'])['volume'].cumsum() df_towels['pct_change_yoy_vol'] = df_towels.groupby(['month'])['Exports_YTD_vol'].pct_change()*100 #filtering data of fiscal year 2020-21 df_towels_2020_21 = df_towels.loc[df_towels['Fiscal Year'].isin(['2020-2021'])] df_towels_2021_22 = df_towels.loc[df_towels['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_towels_2020_21['month'], y=df_towels_2020_21['Exports_YTD_vol'], name='Exports in 2020-21', text=df_towels_2020_21['Exports_YTD_vol'], textposition='auto', texttemplate='%{text:,}', hovertemplate='Exports to date: %{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_towels_2021_22['month'], y=df_towels_2021_22['Exports_YTD_vol'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Exports in 2021-22', text=df_towels_2021_22['Exports_YTD_vol'], textposition='top center', texttemplate="%{text:,}", line=dict(color='Green', width=4), hovertemplate='Exports to date: %{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_towels_2021_22['month'], y=df_towels_2021_22['pct_change_yoy_vol'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_towels_2021_22['pct_change_yoy_vol'], textposition='middle right', texttemplate="%{text:.2f}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='Cumulative Exports (Metric Tons)', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Pakistan Towels Exports by Volume", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ##################################### # towels chart export price df_towels['pct_change_yoy_price'] = df_towels.groupby(['month'])['unit_price'].pct_change()*100 df_towels_2020_21 = df_towels.loc[df_towels['Fiscal Year'].isin(['2020-2021'])] df_towels_2021_22 = df_towels.loc[df_towels['Fiscal Year'].isin(['2021-2022'])] fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_towels_2020_21['month'], y=df_towels_2020_21['unit_price'], name='Price in 2020-21', text=df_towels_2020_21['unit_price'], textposition='auto', texttemplate='$%{text:.2f}', hovertemplate='Exports price:$%{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_towels_2021_22['month'], y=df_towels_2021_22['unit_price'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Price in 2021-22', text=df_towels_2021_22['unit_price'], textposition='bottom right', texttemplate="$%{text:.2f}", line=dict(color='Green', width=4), hovertemplate='Exports price:$%{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_towels_2021_22['month'], y=df_towels_2021_22['pct_change_yoy_price'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_towels_2021_22['pct_change_yoy_price'], textposition='middle right', texttemplate="%{text:.2s}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) #fig_ytd.update_yaxes(title_text="Cumulative Exports in US$") image = Image.open('logo.png') #st.image(logo.png) fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='US$ per Kg', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Pakistan Towels Average Export Price", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ##################################### elif page == 'Total Textile Exports': #st.title("Pakistan Textile Exports") #importing csv file as dataframe df = pd.read_csv('monthly_textile_exports_pbs.csv') #df # to see dataframe #df #convert date columns into datetime format #to convert big numbers to M, B, df['date'] = pd.to_datetime(df['date'], infer_datetime_format=True) df['year'] = df['date'].dt.year #creates a year column out of datetime columns df['month'] = df['date'].dt.month #creates a month column out of datetime columns df['year'] = df['year'].astype('string') #converting year column into string for filtering df['month'] = df['month'].astype('string') #converting year column into string for filtering #grouping all categories of exports in monthly frequency, preserving datetime index df_monthly_sum = df.groupby(pd.Grouper(key = 'date', freq='1M')).sum().reset_index() #adding 'Fiscal Year' columns df_monthly_sum['Fiscal Year'] = df_monthly_sum['date'].dt.to_period('Q-JUN').dt.qyear.apply(lambda x: str(x-1) + "-" + str(x)) #adding month column df_monthly_sum['month'] = df_monthly_sum['date'].dt.strftime('%b') #creating month names column #calculating year-to-date YTD exports df_monthly_sum['Exports_YTD'] = df_monthly_sum.groupby(['Fiscal Year'])['Exports_US$'].cumsum() df_monthly_sum['pct_change_yoy'] = df_monthly_sum.groupby(['month'])['Exports_YTD'].pct_change()*100 #filtering data of fiscal year 2021-22 df_2021_22 = df_monthly_sum.loc[df_monthly_sum['Fiscal Year'].isin(['2021-2022'])] #filtering data of fiscal year 2020-21 df_2020_21 = df_monthly_sum.loc[df_monthly_sum['Fiscal Year'].isin(['2020-2021'])] ####################################### ###################################### ######################################## #Year to date chart of fiscal year ######################################### fig_ytd = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.01, row_heights=[0.20,0.80]) #fig_ytd = go.Figure() #fig_ytd = make_subplots(specs=[[{'secondary_y': True}]], rows=1, cols=1) # to make subplot with 1 row and 1 col # Add traces fig_ytd.add_trace(go.Bar(x=df_2020_21['month'], y=df_2020_21['Exports_YTD'], name='Exports in 2020-21', text=df_2020_21['Exports_YTD'], textposition='auto', texttemplate='%{text:,}', hovertemplate='Exports to date: %{y}' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_2021_22['month'], y=df_2021_22['Exports_YTD'], mode='markers+lines+text', marker=dict(size=16, color="Green"), name='Exports in 2021-22', text=df_2021_22['Exports_YTD'], textposition='top center', texttemplate="%{text:,}", line=dict(color='Green', width=4), hovertemplate='Exports to date: %{y}B' ), row=2, col=1) fig_ytd.add_trace(go.Scatter(x=df_2021_22['month'], y=df_2021_22['pct_change_yoy'], mode="lines+markers+text", marker=dict(size=16, color="Red"), name="%Change from previous year", text=df_2021_22['pct_change_yoy'], textposition='middle right', texttemplate="%{text:.2s}%", line=dict(color='Red', width=1, dash='dash'), hovertemplate='%{y}', ), row=1, col=1 ) image = Image.open('logo.png') fig_ytd.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.2, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) fig_ytd.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=110, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig_ytd.update_xaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_yaxes(visible=False, row=1, col=1 ) #range=[0, 100] if need to set y-axis range fig_ytd.update_yaxes(showline=True, linewidth=2, linecolor='black', row=2, col=1 ) fig_ytd.update_xaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=24)) fig_ytd.update_yaxes(title='Cumulative Exports (US$ Billion)', title_font=dict(family='Roboto', color='black', size=20), row=2, col=1) fig_ytd.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') ############### #title fig_ytd.add_annotation( text="Total Textile Exports from Pakistan", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0, y=1.18, showarrow=False, arrowhead=1) #subtitle fig_ytd.add_annotation( text="current year vs. previous year", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=0, y=1.10, showarrow=False, arrowhead=1) #data reference fig_ytd.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0, y=-0.2, showarrow=False, arrowhead=1) fig_ytd.update_layout(legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 )) st.plotly_chart(fig_ytd, use_container_width=True) # to show Figure; container width true makes fig. size responsive ################################# ############################### #summary of current year #adding 'Fiscal Year' columns df['Fiscal Year'] = df['date'].dt.to_period('Q-JUN').dt.qyear.apply(lambda x: str(x-1) + "-" + str(x)) #adding month column df['month'] = df['date'].dt.strftime('%b') #creating month names column #calculating year-to-date YTD exports df = df.groupby(['Fiscal Year', 'category'])['Exports_US$'].sum().reset_index() df['pct_change_yoy'] = df.groupby(['category'])['Exports_US$'].pct_change()*100 #filtering data of fiscal year 2021-22 df_2021_22 = df.loc[df['Fiscal Year'].isin(['2021-2022'])] #filtering data of fiscal year 2020-21 df_2020_21 = df.loc[df['Fiscal Year'].isin(['2020-2021'])] fig = go.Figure() # fig = make_subplots(rows=1, cols=1) # to make subplot with 1 row and 1 col fig.add_trace(go.Bar(x=df_2021_22['Exports_US$'], y=df_2021_22['category'], text=df_2021_22['Exports_US$'], textposition='auto', texttemplate='$%{text:,}', hovertemplate='%{x}', name='Exports US$', orientation='h', )) fig.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=80, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig.update_xaxes(showline=True, linewidth=2, linecolor='black') fig.update_yaxes(showline=True, linewidth=2, linecolor='black') fig.update_xaxes(title='Exports in US$ Billion', title_font=dict(family='Roboto', color='black', size=20)) fig.update_yaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=20)) fig.update_xaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') fig.update_yaxes({'categoryorder':'total ascending'}) ############### #title fig.add_annotation( text="Category-wise Textile Exports from Pakistan", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=-0.1, y=1.18, showarrow=False, arrowhead=1) #subtitle fig.add_annotation( text="current financial year to date", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=-0.1, y=1.09, showarrow=False, arrowhead=1) #data reference fig.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=-0.1, y=-0.15, showarrow=False, arrowhead=1) image = Image.open('logo.png') fig.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.15, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) st.plotly_chart(fig, use_container_width=True) # to show Figure; container width true makes fig. size responsive ######################### # 2020-21 fig = go.Figure() # fig = make_subplots(rows=1, cols=1) # to make subplot with 1 row and 1 col fig.add_trace(go.Bar(x=df_2020_21['Exports_US$'], y=df_2020_21['category'], text=df_2020_21['Exports_US$'], textposition='auto', texttemplate='$%{text:,}', hovertemplate='%{x}', name='Exports US$', orientation='h', )) fig.update_layout( autosize=True, height=650, width=1050, legend_traceorder="reversed", margin=dict(t=90, b=80, l=90, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), xaxis_title='', yaxis_title="", plot_bgcolor='#ffffff', paper_bgcolor='#ffffff', font=dict(color='#111111', size=18, family="roboto, sans-serif"), #font of lablels of axises ) #updates axes fig.update_xaxes(showline=True, linewidth=2, linecolor='black') fig.update_yaxes(showline=True, linewidth=2, linecolor='black') fig.update_xaxes(title='Exports in US$ Billion', title_font=dict(family='Roboto', color='black', size=20)) fig.update_yaxes(tickangle=0, tickfont=dict(family='Roboto', color='black', size=20)) fig.update_xaxes(showgrid=True, gridwidth=1, gridcolor='#758D99') fig.update_yaxes({'categoryorder':'total ascending'}) ############### #title fig.add_annotation( text="Category-wise Textile Exports from Pakistan", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=-0.1, y=1.18, showarrow=False, arrowhead=1) #subtitle fig.add_annotation( text="Financial year 2020-21", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=-0.1, y=1.09, showarrow=False, arrowhead=1) #data reference fig.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=-0.1, y=-0.15, showarrow=False, arrowhead=1) image = Image.open('logo.png') fig.add_layout_image( dict( source=image, xref="paper", yref="paper", x=1, y=-0.15, #image postion on chart sizex=0.1, sizey=0.1, #image size on chart xanchor="right", yanchor="bottom" )) st.plotly_chart(fig, use_container_width=True) # to show Figure; container width true makes fig. size responsive #################################### # pie chart ## creating df containing only yearly aggregate of exports df_yearly = df.groupby(['Fiscal Year']).agg(**{'Exports_US$_sum': ('Exports_US$', 'sum')}).reset_index() #groupby year, then category # setting first name as index column df_yearly.set_index("Fiscal Year", inplace = True) #getting exact value of exports in each year exports_2020_21=df_yearly.loc['2020-2021']['Exports_US$_sum'] exports_2021_22=df_yearly.loc['2021-2022']['Exports_US$_sum'] import plotly.express as px fig = px.pie(df_2020_21, values='Exports_US$', names='category', color='category', labels={"category":"Category"}, hole=0.7, template='plotly' ) fig.update_traces(textposition='outside', textinfo='value+percent+label', marker=dict(line=dict(color='#111111', width=0.5)), #color and size of lines between slices pull=[0, 0, 0, 0], opacity=1, rotation=170, automargin=True) #increasing value of pull from 0-1 will pull a slice out fig.update_layout( autosize=True, height=700, width=1100, margin=dict(t=90, b=0, l=40, r=20), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), plot_bgcolor='#ededed', paper_bgcolor='#ffffff', font=dict(color='#111111', size=16, family="roboto, sans-serif"), #font of lablels of axises ) #title fig.add_annotation( text="Pakistan Textile Exports", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=-0.35, y=1.17, showarrow=False, arrowhead=1) #subtitle fig.add_annotation( text="Financial year 2020-21", font=dict(family='roboto', color='black', size=24), xref="paper", yref="paper", x=-0.35, y=1.09, showarrow=False, arrowhead=1) #data reference fig.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=1.3, y=-0.2, showarrow=False, arrowhead=1) image = Image.open('logo.png') fig.add_layout_image( dict( source=image, xref="paper", yref="paper", x=-0.2, y=-0.2, #image postion on chart sizex=0.15, sizey=0.15, #image size on chart xanchor="right", yanchor="bottom" )) fig.add_annotation( #number = str("{:,}".format(number)) , to fomat with comma separator text="Total: $" + str("{:,}".format(exports_2020_21)), #variable value is printed inside piechart only as string font=dict(color='#111111', size=36, family="roboto, sans-serif"), showarrow=False, arrowhead=1) fig.update_layout(legend=dict( yanchor="top", y=0.6, xanchor="left", x=1 )) st.plotly_chart(fig, use_container_width=True) # to show Figure; container width true makes fig. size responsive ####################### #dashboard ####################### else: index=0 df = pd.read_csv('monthly_textile_exports_pbs.csv') df['date'] = pd.to_datetime(df['date'], infer_datetime_format=True) df['year'] = df['date'].dt.year #creates a year column out of datetime columns df['month'] = df['date'].dt.month #creates a month column out of datetime columns df['year'] = df['year'].astype('string') #converting year column into string for filtering df['month'] = df['month'].astype('string') #converting year column into string for filtering #grouping all categories of exports in monthly frequency, preserving datetime index df_monthly_sum = df.groupby(pd.Grouper(key = 'date', freq='1M')).sum().reset_index() #adding 'Fiscal Year' columns df_monthly_sum['Fiscal Year'] = df_monthly_sum['date'].dt.to_period('Q-JUN').dt.qyear.apply(lambda x: str(x-1) + "-" + str(x)) #adding month column df_monthly_sum['month'] = df_monthly_sum['date'].dt.strftime('%b') #creating month names column #calculating year-to-date YTD exports df_monthly_sum['Exports_YTD'] = df_monthly_sum.groupby(['Fiscal Year'])['Exports_US$'].cumsum() df_monthly_sum['pct_change_yoy'] = df_monthly_sum.groupby(['month'])['Exports_YTD'].pct_change()*100 #filtering data of fiscal year 2021-22 df_2021_22 = df_monthly_sum.loc[df_monthly_sum['Fiscal Year'].isin(['2021-2022'])] #filtering data of fiscal year 2020-21 df_2020_21 = df_monthly_sum.loc[df_monthly_sum['Fiscal Year'].isin(['2020-2021'])] ####################################### df['year'] = df['year'].astype('string') #converting year column into string for filtering df['month'] = df['month'].astype('string') #converting year column into string for filtering df['Fiscal Year'] = df['date'].dt.to_period('Q-JUN').dt.qyear.apply(lambda x: str(x-1) + "-" + str(x)) #adding month column df['month'] = df['date'].dt.strftime('%b') #creating month names column ##################################### df_towels = df.loc[df['category'].isin(['Towels'])] df_towels['Exports_YTD'] = df_towels.groupby(['Fiscal Year'])['Exports_US$'].cumsum() df_towels['pct_change_yoy'] = df_towels.groupby(['month'])['Exports_YTD'].pct_change()*100 df_towels['Exports_YTD_vol'] = df_towels.groupby(['Fiscal Year'])['volume'].cumsum() df_towels['pct_change_yoy_vol'] = df_towels.groupby(['month'])['Exports_YTD_vol'].pct_change()*100 ###################################### df_knitwear = df.loc[df['category'].isin(['Knitwear'])] df_knitwear['Exports_YTD'] = df_knitwear.groupby(['Fiscal Year'])['Exports_US$'].cumsum() df_knitwear['pct_change_yoy'] = df_knitwear.groupby(['month'])['Exports_YTD'].pct_change()*100 df_knitwear['Exports_YTD_vol'] = df_knitwear.groupby(['Fiscal Year'])['volume'].cumsum() df_knitwear['pct_change_yoy_vol'] = df_knitwear.groupby(['month'])['Exports_YTD_vol'].pct_change()*100 df_knitwear['pct_change_yoy_price'] = df_knitwear.groupby(['month'])['unit_price'].pct_change()*100 ###################################### df_bedwear = df.loc[df['category'].isin(['Bedwear'])] df_bedwear['Exports_YTD'] = df_bedwear.groupby(['Fiscal Year'])['Exports_US$'].cumsum() df_bedwear['pct_change_yoy'] = df_bedwear.groupby(['month'])['Exports_YTD'].pct_change()*100 df_bedwear['Exports_YTD_vol'] = df_bedwear.groupby(['Fiscal Year'])['volume'].cumsum() df_bedwear['pct_change_yoy_vol'] = df_bedwear.groupby(['month'])['Exports_YTD_vol'].pct_change()*100 ###################################### df_garments = df.loc[df['category'].isin(['Garments'])] df_garments['Exports_YTD'] = df_garments.groupby(['Fiscal Year'])['Exports_US$'].cumsum() df_garments['pct_change_yoy'] = df_garments.groupby(['month'])['Exports_YTD'].pct_change()*100 df_garments['Exports_YTD_vol'] = df_garments.groupby(['Fiscal Year'])['volume'].cumsum() df_garments['pct_change_yoy_vol'] = df_garments.groupby(['month'])['Exports_YTD_vol'].pct_change()*100 ###################################### df_cloth = df.loc[df['category'].isin(['Cotton Cloth'])] df_cloth['Exports_YTD'] = df_cloth.groupby(['Fiscal Year'])['Exports_US$'].cumsum() df_cloth['pct_change_yoy'] = df_cloth.groupby(['month'])['Exports_YTD'].pct_change()*100 df_cloth['Exports_YTD_vol'] = df_cloth.groupby(['Fiscal Year'])['volume'].cumsum() df_cloth['pct_change_yoy_vol'] = df_cloth.groupby(['month'])['Exports_YTD_vol'].pct_change()*100 ###################################### df_cyarn = df.loc[df['category'].isin(['Cotton Yarn'])] df_cyarn['Exports_YTD'] = df_cyarn.groupby(['Fiscal Year'])['Exports_US$'].cumsum() df_cyarn['pct_change_yoy'] = df_cyarn.groupby(['month'])['Exports_YTD'].pct_change()*100 df_cyarn['Exports_YTD_vol'] = df_cyarn.groupby(['Fiscal Year'])['volume'].cumsum() df_cyarn['pct_change_yoy_vol'] = df_cyarn.groupby(['month'])['Exports_YTD_vol'].pct_change()*100 ###################################### df_madeup = df.loc[df['category'].isin(['Madeups'])] df_madeup['Exports_YTD'] = df_madeup.groupby(['Fiscal Year'])['Exports_US$'].cumsum() df_madeup['pct_change_yoy'] = df_madeup.groupby(['month'])['Exports_YTD'].pct_change()*100 df_madeup['Exports_YTD_vol'] = df_madeup.groupby(['Fiscal Year'])['volume'].cumsum() df_madeup['pct_change_yoy_vol'] = df_madeup.groupby(['month'])['Exports_YTD_vol'].pct_change()*100 ###################################### df_other = df.loc[df['category'].isin(['Other Textiles'])] df_other['Exports_YTD'] = df_other.groupby(['Fiscal Year'])['Exports_US$'].cumsum() df_other['pct_change_yoy'] = df_other.groupby(['month'])['Exports_YTD'].pct_change()*100 df_other['Exports_YTD_vol'] = df_other.groupby(['Fiscal Year'])['volume'].cumsum() df_other['pct_change_yoy_vol'] = df_other.groupby(['month'])['Exports_YTD_vol'].pct_change()*100 ###################################### df_ass = df.loc[df['category'].isin(['Artificial Silk & Synthetics'])] df_ass['Exports_YTD'] = df_ass.groupby(['Fiscal Year'])['Exports_US$'].cumsum() df_ass['pct_change_yoy'] = df_ass.groupby(['month'])['Exports_YTD'].pct_change()*100 df_ass['Exports_YTD_vol'] = df_ass.groupby(['Fiscal Year'])['volume'].cumsum() df_ass['pct_change_yoy_vol'] = df_ass.groupby(['month'])['Exports_YTD_vol'].pct_change()*100 ###################################### df_tt = df.loc[df['category'].isin(['Tents, Tarpaulines'])] df_tt['Exports_YTD'] = df_tt.groupby(['Fiscal Year'])['Exports_US$'].cumsum() df_tt['pct_change_yoy'] = df_tt.groupby(['month'])['Exports_YTD'].pct_change()*100 df_tt['Exports_YTD_vol'] = df_tt.groupby(['Fiscal Year'])['volume'].cumsum() df_tt['pct_change_yoy_vol'] = df_tt.groupby(['month'])['Exports_YTD_vol'].pct_change()*100 ###################################### df_ncyarn = df.loc[df['category'].isin(['Non-Cotton Yarn'])] df_ncyarn['Exports_YTD'] = df_ncyarn.groupby(['Fiscal Year'])['Exports_US$'].cumsum() df_ncyarn['pct_change_yoy'] = df_ncyarn.groupby(['month'])['Exports_YTD'].pct_change()*100 df_ncyarn['Exports_YTD_vol'] = df_ncyarn.groupby(['Fiscal Year'])['volume'].cumsum() df_ncyarn['pct_change_yoy_vol'] = df_ncyarn.groupby(['month'])['Exports_YTD_vol'].pct_change()*100 ###################################### df_rcotton = df.loc[df['category'].isin(['Raw Cotton'])] df_rcotton['Exports_YTD'] = df_rcotton.groupby(['Fiscal Year'])['Exports_US$'].cumsum() df_rcotton['pct_change_yoy'] = df_rcotton.groupby(['month'])['Exports_YTD'].pct_change()*100 df_rcotton['Exports_YTD_vol'] = df_rcotton.groupby(['Fiscal Year'])['volume'].cumsum() df_rcotton['pct_change_yoy_vol'] = df_rcotton.groupby(['month'])['Exports_YTD_vol'].pct_change()*100 ###################################### df_crdcotton = df.loc[df['category'].isin(['Cotton Crd/Cmd'])] df_crdcotton['Exports_YTD'] = df_crdcotton.groupby(['Fiscal Year'])['Exports_US$'].cumsum() df_crdcotton['pct_change_yoy'] = df_crdcotton.groupby(['month'])['Exports_YTD'].pct_change()*100 df_crdcotton['Exports_YTD_vol'] = df_crdcotton.groupby(['Fiscal Year'])['volume'].cumsum() df_crdcotton['pct_change_yoy_vol'] = df_crdcotton.groupby(['month'])['Exports_YTD_vol'].pct_change()*100 #dashboard recent_month = df_monthly_sum.month.iloc[-1] #Exports_YTD column ytd_total = df_monthly_sum.Exports_YTD.iloc[-1] pct_total = df_monthly_sum.Exports_YTD.iloc[-13] ########### ytd_knitwear = df_knitwear.Exports_YTD.iloc[-1] pct_knitwear = df_knitwear.Exports_YTD.iloc[-13] ########### ytd_bedwear = df_bedwear.Exports_YTD.iloc[-1] pct_bedwear = df_bedwear.Exports_YTD.iloc[-13] ########### ytd_garments = df_garments.Exports_YTD.iloc[-1] pct_garments = df_garments.Exports_YTD.iloc[-13] ########### ytd_cloth = df_cloth.Exports_YTD.iloc[-1] pct_cloth = df_cloth.Exports_YTD.iloc[-13] ########### ytd_cyarn = df_cyarn.Exports_YTD.iloc[-1] pct_cyarn = df_cyarn.Exports_YTD.iloc[-13] ########### ytd_towel = df_towels.Exports_YTD.iloc[-1] pct_towel = df_towels.Exports_YTD.iloc[-13] ########### ytd_madeups = df_madeup.Exports_YTD.iloc[-1] pct_madeups = df_madeup.Exports_YTD.iloc[-13] ########### ytd_other = df_other.Exports_YTD.iloc[-1] pct_other = df_other.Exports_YTD.iloc[-13] ########### ytd_ass = df_ass.Exports_YTD.iloc[-1] pct_ass = df_ass.Exports_YTD.iloc[-13] ########### ytd_tt = df_tt.Exports_YTD.iloc[-1] pct_tt = df_tt.Exports_YTD.iloc[-13] ########### ytd_ncyarn = df_ncyarn.Exports_YTD.iloc[-1] pct_ncyarn = df_ncyarn.Exports_YTD.iloc[-13] ########### ytd_rcotton = df_rcotton.Exports_YTD.iloc[-1] pct_rcotton = df_rcotton.Exports_YTD.iloc[-13] ########### ytd_crdcotton = df_crdcotton.Exports_YTD.iloc[-1] pct_crdcotton = df_crdcotton.Exports_YTD.iloc[-13] #############voluem ########### ytd_knitwear_v = df_knitwear.Exports_YTD_vol.iloc[-1] pct_knitwear_v = df_knitwear.Exports_YTD_vol.iloc[-13] ########### ytd_bedwear_v = df_bedwear.Exports_YTD_vol.iloc[-1] pct_bedwear_v = df_bedwear.Exports_YTD_vol.iloc[-13] ########### ytd_garments_v = df_garments.Exports_YTD_vol.iloc[-1] pct_garments_v = df_garments.Exports_YTD_vol.iloc[-13] ########### ytd_cloth_v = df_cloth.Exports_YTD_vol.iloc[-1] pct_cloth_v = df_cloth.Exports_YTD_vol.iloc[-13] ########### ytd_cyarn_v = df_cyarn.Exports_YTD_vol.iloc[-1] pct_cyarn_v = df_cyarn.Exports_YTD_vol.iloc[-13] ########### ytd_towel_v = df_towels.Exports_YTD_vol.iloc[-1] pct_towel_v = df_towels.Exports_YTD_vol.iloc[-13] ########### ########### ytd_other_v = df_other.Exports_YTD_vol.iloc[-1] pct_other_v = df_other.Exports_YTD_vol.iloc[-13] ########### ytd_ass_v = df_ass.Exports_YTD_vol.iloc[-1] pct_ass_v = df_ass.Exports_YTD_vol.iloc[-13] ########### ytd_tt_v = df_tt.Exports_YTD_vol.iloc[-1] pct_tt_v = df_tt.Exports_YTD_vol.iloc[-13] ########### ytd_ncyarn_v = df_ncyarn.Exports_YTD_vol.iloc[-1] pct_ncyarn_v = df_ncyarn.Exports_YTD_vol.iloc[-13] ########### ytd_rcotton_v = df_rcotton.Exports_YTD_vol.iloc[-1] pct_rcotton_v = df_rcotton.Exports_YTD_vol.iloc[-13] ########### ytd_crdcotton_v = df_crdcotton.Exports_YTD_vol.iloc[-1] pct_crdcotton_v = df_crdcotton.Exports_YTD_vol.iloc[-13] #############unit price ########### ytd_knitwear_p = df_knitwear.unit_price.iloc[-1] pct_knitwear_p = df_knitwear.unit_price.iloc[-13] ########### ytd_bedwear_p = df_bedwear.unit_price.iloc[-1] pct_bedwear_p = df_bedwear.unit_price.iloc[-13] ########### ytd_garments_p = df_garments.unit_price.iloc[-1] pct_garments_p = df_garments.unit_price.iloc[-13] ########### ytd_cloth_p = df_cloth.unit_price.iloc[-1] pct_cloth_p = df_cloth.unit_price.iloc[-13] ########### ytd_cyarn_p = df_cyarn.unit_price.iloc[-1] pct_cyarn_p = df_cyarn.unit_price.iloc[-13] ########### ytd_towel_p = df_towels.unit_price.iloc[-1] pct_towel_p = df_towels.unit_price.iloc[-13] ########### ########### ytd_other_p = df_other.unit_price.iloc[-1] pct_other_p = df_other.unit_price.iloc[-13] ########### ytd_ass_p = df_ass.unit_price.iloc[-1] pct_ass_p = df_ass.unit_price.iloc[-13] ########### ytd_tt_p = df_tt.unit_price.iloc[-1] pct_tt_p = df_tt.unit_price.iloc[-13] ########### ytd_ncyarn_p = df_ncyarn.unit_price.iloc[-1] pct_ncyarn_p = df_ncyarn.unit_price.iloc[-13] ########### ytd_rcotton_p = df_rcotton.unit_price.iloc[-1] pct_rcotton_p = df_rcotton.unit_price.iloc[-13] ########### ytd_crdcotton_p = df_crdcotton.unit_price.iloc[-1] pct_crdcotton_p = df_crdcotton.unit_price.iloc[-13] #st.header(f'Pakistan Exports Jun-{recent_month} 2021-22') ################################### ################################### # value indicators fig = go.Figure() fig.update_layout( grid = {'rows': 4, 'columns': 4, 'pattern': "independent"}) fig.add_trace(go.Indicator( value=ytd_total, mode="number+delta", number={'prefix': "$", "font":{"size":50, "color":'#11b81f', "family":"helvetica neue"}}, title={"text": "TOTAL"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_total, 'valueformat': '.0%', 'relative':True}, domain = {'row': 0, 'column': 0} )) fig.add_trace(go.Indicator( value=ytd_knitwear, mode="number+delta", number={'prefix': "$", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Knitwear"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_knitwear, 'valueformat': '.0%', 'relative':True}, domain = {'row': 0, 'column': 1} )) fig.add_trace(go.Indicator( value=ytd_garments, mode="number+delta", number={'prefix': "$", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Garments"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_garments, 'valueformat': '.0%', 'relative':True}, domain = {'row': 0, 'column': 2} )) fig.add_trace(go.Indicator( value=ytd_bedwear, mode="number+delta", number={'prefix': "$", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Bedwear"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_bedwear, 'valueformat': '.0%', 'relative':True}, domain = {'row': 0, 'column': 3} )) fig.add_trace(go.Indicator( value=ytd_cloth, mode="number+delta", number={'prefix': "$", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Cotton Cloth"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_cloth, 'valueformat': '.0%', 'relative':True}, domain = {'row': 1, 'column': 0} )) fig.add_trace(go.Indicator( value=ytd_cyarn, mode="number+delta", number={'prefix': "$", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Cotton Yarn"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_cyarn, 'valueformat': '.0%', 'relative':True}, domain = {'row': 1, 'column': 1} )) fig.add_trace(go.Indicator( value=ytd_towel, mode="number+delta", number={'prefix': "$", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Towels"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_towel, 'valueformat': '.0%', 'relative':True}, domain = {'row': 1, 'column': 2} )) fig.add_trace(go.Indicator( value=ytd_madeups, mode="number+delta", number={'prefix': "$", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Madeups"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_madeups, 'valueformat': '.0%', 'relative':True}, domain = {'row': 1, 'column': 3} )) fig.add_trace(go.Indicator( value=ytd_other, mode="number+delta", number={'prefix': "$", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Other Textiles"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_other, 'valueformat': '.0%', 'relative':True}, domain = {'row': 2, 'column': 0} )) fig.add_trace(go.Indicator( value=ytd_ass, mode="number+delta", number={'prefix': "$", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Art. Silk & Synthetics"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_ass, 'valueformat': '.0%', 'relative':True}, domain = {'row': 2, 'column': 1} )) fig.add_trace(go.Indicator( value=ytd_tt, mode="number+delta", number={'prefix': "$", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Tents, Tarpaulines"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_tt, 'valueformat': '.0%', 'relative':True}, domain = {'row': 2, 'column': 2} )) fig.add_trace(go.Indicator( value=ytd_ncyarn, mode="number+delta", number={'prefix': "$", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Non-Cotton Yarn"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_ncyarn, 'valueformat': '.0%', 'relative':True}, domain = {'row': 2, 'column': 3} )) fig.add_trace(go.Indicator( value=ytd_rcotton, mode="number+delta", number={'prefix': "$", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Raw Cotton"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_rcotton, 'valueformat': '.0%', 'relative':True}, domain = {'row': 3, 'column': 0} )) fig.add_trace(go.Indicator( value=ytd_crdcotton, mode="number+delta", number={'prefix': "$", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Carded/Combed Cotton"}, title_font=dict(size=25, color='#e05020', family="roboto"), #delta={'reference':pct_crdcotton, 'valueformat': '.0%', 'relative':True}, domain = {'row': 3, 'column': 1} )) #fig.update_layout(height = 600) #changing this will adjust gap between rows fig.add_annotation( text=f"Pakistan Textile Exports by Value: Jul-{recent_month} 2021-22", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0.5, y=1.17, showarrow=False, arrowhead=1) fig.update_layout( autosize=True, height=650, width=1100, margin=dict(t=100, b=20, l=40, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), plot_bgcolor='#ededed', paper_bgcolor='#ffffff', font=dict(color='#006BA2', size=16, family="roboto, sans-serif"), #font of lablels of axises ) #data reference fig.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0.96, y=0, showarrow=False, arrowhead=1) image = Image.open('logo.png') fig.add_layout_image( dict( source=image, xref="paper", yref="paper", x=0.96, y=0.1, #image postion on chart sizex=0.15, sizey=0.15, #image size on chart xanchor="right", yanchor="bottom" )) st.plotly_chart(fig, use_container_width=True) ################################### ################################### # value indicators fig = go.Figure() fig.update_layout( grid = {'rows': 4, 'columns': 4, 'pattern': "independent"}) fig.add_trace(go.Indicator( value=ytd_knitwear_v, mode="number+delta", number={'suffix': ", D", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Knitwear"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_knitwear_v, 'valueformat': '.0%', 'relative':True}, domain = {'row': 0, 'column': 0} )) fig.add_trace(go.Indicator( value=ytd_garments_v, mode="number+delta", number={'suffix': ", D", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Garments"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_garments_v, 'valueformat': '.0%', 'relative':True}, domain = {'row': 0, 'column': 1} )) fig.add_trace(go.Indicator( value=ytd_bedwear_v, mode="number+delta", number={'suffix': ", T", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Bedwear"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_bedwear_v, 'valueformat': '.0%', 'relative':True}, domain = {'row': 0, 'column': 2} )) fig.add_trace(go.Indicator( value=ytd_cloth_v, mode="number+delta", number={'suffix': ", T", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Cotton Cloth"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_cloth_v, 'valueformat': '.0%', 'relative':True}, domain = {'row': 0, 'column': 3} )) fig.add_trace(go.Indicator( value=ytd_cyarn_v, mode="number+delta", number={'suffix': ", T", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Cotton Yarn"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_cyarn_v, 'valueformat': '.0%', 'relative':True}, domain = {'row': 1, 'column': 0} )) fig.add_trace(go.Indicator( value=ytd_towel_v, mode="number+delta", number={'suffix': ", T", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Towels"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_towel_v, 'valueformat': '.0%', 'relative':True}, domain = {'row': 1, 'column': 1} )) fig.add_trace(go.Indicator( value=ytd_ass_v, mode="number+delta", number={'suffix': ", T", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Art. Silk & Synthetics"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_ass_v, 'valueformat': '.0%', 'relative':True}, domain = {'row': 1, 'column': 2} )) fig.add_trace(go.Indicator( value=ytd_tt_v, mode="number+delta", number={'suffix': ", T", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Tents, Tarpaulines"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_tt_v, 'valueformat': '.0%', 'relative':True}, domain = {'row': 1, 'column': 3} )) fig.add_trace(go.Indicator( value=ytd_ncyarn_v, mode="number+delta", number={'suffix': ", T", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Non-Cotton Yarn"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_ncyarn_v, 'valueformat': '.0%', 'relative':True}, domain = {'row': 2, 'column': 0} )) fig.add_trace(go.Indicator( value=ytd_rcotton_v, mode="number+delta", number={'suffix': ", T", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Raw Cotton"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_rcotton_v, 'valueformat': '.0%', 'relative':True}, domain = {'row': 2, 'column': 1} )) fig.add_trace(go.Indicator( value=ytd_crdcotton_v, mode="number+delta", number={'suffix': ", T", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Carded/Combed Cotton"}, title_font=dict(size=25, color='#e05020', family="roboto"), #delta={'reference':pct_crdcotton, 'valueformat': '.0%', 'relative':True}, domain = {'row': 2, 'column': 2} )) #fig.update_layout(height = 600) #changing this will adjust gap between rows fig.add_annotation( text=f"Pakistan Textile Exports by Volume: Jul-{recent_month} 2021-22", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0.5, y=1.17, showarrow=False, arrowhead=1) fig.update_layout( autosize=True, height=650, width=1100, margin=dict(t=100, b=20, l=40, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), plot_bgcolor='#ededed', paper_bgcolor='#ffffff', font=dict(color='#006BA2', size=16, family="roboto, sans-serif"), #font of lablels of axises ) #data reference fig.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0.96, y=0, showarrow=False, arrowhead=1) image = Image.open('logo.png') fig.add_layout_image( dict( source=image, xref="paper", yref="paper", x=0.96, y=0.1, #image postion on chart sizex=0.15, sizey=0.15, #image size on chart xanchor="right", yanchor="bottom" )) st.plotly_chart(fig, use_container_width=True) ################################### ################################### # price indicators fig = go.Figure() fig.update_layout( grid = {'rows': 4, 'columns': 4, 'pattern': "independent"}) fig.add_trace(go.Indicator( value=ytd_knitwear_p, mode="number+delta", number={'suffix': ", $/D", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Knitwear"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_knitwear_p, 'valueformat': '.0%', 'relative':True}, domain = {'row': 0, 'column': 0} )) fig.add_trace(go.Indicator( value=ytd_garments_p, mode="number+delta", number={'suffix': ", $/D", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Garments"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_garments_p, 'valueformat': '.0%', 'relative':True}, domain = {'row': 0, 'column': 1} )) fig.add_trace(go.Indicator( value=ytd_bedwear_p, mode="number+delta", number={'suffix': ", $/Kg", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Bedwear"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_bedwear_p, 'valueformat': '.0%', 'relative':True}, domain = {'row': 0, 'column': 2} )) fig.add_trace(go.Indicator( value=ytd_cloth_p, mode="number+delta", number={'suffix': ", $/Kg", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Cotton Cloth"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_cloth_p, 'valueformat': '.0%', 'relative':True}, domain = {'row': 0, 'column': 3} )) fig.add_trace(go.Indicator( value=ytd_cyarn_p, mode="number+delta", number={'suffix': ", $/Kg", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Cotton Yarn"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_cyarn_p, 'valueformat': '.0%', 'relative':True}, domain = {'row': 1, 'column': 0} )) fig.add_trace(go.Indicator( value=ytd_towel_p, mode="number+delta", number={'suffix': ", $/Kg", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Towels"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_towel_p, 'valueformat': '.0%', 'relative':True}, domain = {'row': 1, 'column': 1} )) fig.add_trace(go.Indicator( value=ytd_ass_p, mode="number+delta", number={'suffix': ", $/Kg", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Art. Silk & Synthetics"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_ass_p, 'valueformat': '.0%', 'relative':True}, domain = {'row': 1, 'column': 2} )) fig.add_trace(go.Indicator( value=ytd_tt_p, mode="number+delta", number={'suffix': ", $/Kg", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Tents, Tarpaulines"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_tt_p, 'valueformat': '.0%', 'relative':True}, domain = {'row': 1, 'column': 3} )) fig.add_trace(go.Indicator( value=ytd_ncyarn_p, mode="number+delta", number={'suffix': ", $/Kg", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Non-Cotton Yarn"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_ncyarn_p, 'valueformat': '.0%', 'relative':True}, domain = {'row': 2, 'column': 0} )) fig.add_trace(go.Indicator( value=ytd_rcotton_p, mode="number+delta", number={'suffix': ", $/Kg", "font":{"size":50, "color":'#000000', "family":"helvetica neue"}}, title={"text": "Raw Cotton"}, title_font=dict(size=25, color='#e05020', family="roboto"), delta={'reference':pct_rcotton_p, 'valueformat': '.0%', 'relative':True}, domain = {'row': 2, 'column': 1} )) #fig.update_layout(height = 600) #changing this will adjust gap between rows fig.add_annotation( text=f"Pakistan Textile Exports by Unit Price: Jul-{recent_month} 2021-22", font=dict(family='Fjalla one', color='#006BA2', size=36), xref="paper", yref="paper", x=0.5, y=1.17, showarrow=False, arrowhead=1) fig.update_layout( autosize=True, height=650, width=1100, margin=dict(t=100, b=20, l=40, r=40), title_font=dict(size=25, color='#111111', family="fjalla one, sans-serif"), plot_bgcolor='#ededed', paper_bgcolor='#ffffff', font=dict(color='#006BA2', size=16, family="roboto, sans-serif"), #font of lablels of axises ) #data reference fig.add_annotation( text="Source: Pakistan Bureau of Statistics", font=dict(family='Fjalla one', color='#758D99', size=20), xref="paper", yref="paper", x=0.96, y=0, showarrow=False, arrowhead=1) image = Image.open('logo.png') fig.add_layout_image( dict( source=image, xref="paper", yref="paper", x=0.96, y=0.1, #image postion on chart sizex=0.15, sizey=0.15, #image size on chart xanchor="right", yanchor="bottom" )) st.plotly_chart(fig, use_container_width=True)

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null

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1

0

1

0

null

0

7

a92f25922ec1f691162b4e61645717b4fdaae639

142

py

Python

djangae/contrib/gauth_sql/backends.py

ikedaosushi/djangae

5fd2f8d70699fbbf155740effe42a36b205a6540

[ "BSD-3-Clause" ]

null

djangae/contrib/gauth_sql/backends.py

ikedaosushi/djangae

5fd2f8d70699fbbf155740effe42a36b205a6540

[ "BSD-3-Clause" ]

null

djangae/contrib/gauth_sql/backends.py

ikedaosushi/djangae

5fd2f8d70699fbbf155740effe42a36b205a6540

[ "BSD-3-Clause" ]

null

from djangae.contrib.gauth.backends import BaseAppEngineUserAPIBackend class AppEngineUserAPIBackend(BaseAppEngineUserAPIBackend): pass

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0.866197

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true

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null

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null

0

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0

1

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7

a96237509e962b7602805547bad34aa79eb9b8ab

47

py

Python

kalliope/neurons/neurotransmitter/__init__.py

joshuaboniface/kalliope

0e040be3165e838485d1e5addc4d2c5df12bfd84

[ "MIT" ]

1

2020-03-30T15:03:19.000Z

kalliope/neurons/neurotransmitter/__init__.py

joshuaboniface/kalliope

0e040be3165e838485d1e5addc4d2c5df12bfd84

[ "MIT" ]

null

kalliope/neurons/neurotransmitter/__init__.py

joshuaboniface/kalliope

0e040be3165e838485d1e5addc4d2c5df12bfd84

[ "MIT" ]

1

2021-11-21T19:08:15.000Z

from .neurotransmitter import Neurotransmitter

23.5

46

0.893617

4

47

10.5

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0.085106

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null

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1

0

1

0

1

0

7

a973c06968df9773fcae3829ccc32d745db5d2f6

3,939

py

Python

neutronpy/models.py

neutronpy/neutronpy

44ca74a0bef25c03397a77aafb359bb257de1fe6

[ "MIT" ]

14

2015-05-08T02:43:46.000Z

2019-05-28T03:47:32.000Z

neutronpy/models.py

neutronpy/neutronpy

44ca74a0bef25c03397a77aafb359bb257de1fe6

[ "MIT" ]

96

2015-02-09T01:04:33.000Z

2020-12-08T22:57:37.000Z

neutronpy/models.py

neutronpy/neutronpy

44ca74a0bef25c03397a77aafb359bb257de1fe6

[ "MIT" ]

5

2016-02-26T22:53:13.000Z

2018-07-16T07:13:04.000Z

# -*- coding: utf-8 -*- r"""Physical Models """ import numpy as np def simple_harmonic_oscillator(p, t): r"""Standard equation for a simple harmonic oscillator Parameters ---------- p : list Parameters, in the following format: +-------+----------------------------+ | p[0] | Constant background | +-------+----------------------------+ | p[1] | Amplitude | +-------+----------------------------+ | p[2] | Period | +-------+----------------------------+ | p[3] | Phase | +-------+----------------------------+ t : ndarray One dimensional input array Returns ------- func : ndarray One dimensional array """ return p[0] + p[1] * np.cos(p[2] * t - p[3]) def damped_harmonic_oscillator(p, t): r"""Standard equation for a damped harmonic oscillator Parameters ---------- p : list Parameters, in the following format: +-------+----------------------------+ | p[0] | Constant background | +-------+----------------------------+ | p[1] | Amplitude | +-------+----------------------------+ | p[2] | Period | +-------+----------------------------+ | p[3] | Phase | +-------+----------------------------+ | p[4] | Damping strength | +-------+----------------------------+ t : ndarray One dimensional input array Returns ------- func : ndarray One dimensional array """ return p[0] + np.exp(-p[4] * t / 2.) * simple_harmonic_oscillator([0, p[1], p[2], p[3]], t) def acoustic_phonon_dispersion(p, x): r"""Standard equation for the dispersion of an acoustic phonon Parameters ---------- p : list Parameters, in the following format: +-------+----------------------------+ | p[0] | Dispersion amplitude | +-------+----------------------------+ | p[1] | Dispersion period | +-------+----------------------------+ x : ndarray One dimensional input array Returns ------- func : ndarray One dimensional array """ return np.sqrt(4 * p[0]) * np.abs(np.sin(p[1] * x)) def optical_phonon_disperion(): r"""Standard equation for the dispersion of an optical phonon """ pass def ferromagnetic_disperion(p, x): r"""Standard equation for the dispersion of a ferromagnetic spin excitation Parameters ---------- p : list Parameters, in the following format: +-------+----------------------------+ | p[0] | Dispersion amplitude | +-------+----------------------------+ | p[1] | Dispersion period | +-------+----------------------------+ x : ndarray One dimensional input array Returns ------- func : ndarray One dimensional array """ return 4 * p[0] * (1 - np.cos(p[1] * x)) def antiferromagnetic_disperion(p, x): r"""Standard equation for the dispersion of an antiferromagnetic spin excitation Parameters ---------- p : list Parameters, in the following format: +-------+----------------------------+ | p[0] | Dispersion amplitude | +-------+----------------------------+ | p[1] | Dispersion period | +-------+----------------------------+ x : ndarray One dimensional input array Returns ------- func : ndarray One dimensional array """ return p[0] * np.abs(np.sin(p[1] * x))

25.577922

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0

null

0

1

0

1

0

7

8d5438acdb1e1fe1060293bbb58df537179c16a8

52

py

Python

config.py

bukun/gislite

8de2d2b0a07dabb0a04476c71d0045ccf555a648

[ "MIT" ]

39

2019-01-21T02:18:33.000Z

2022-03-02T11:15:19.000Z

config.py

bukun/gislite

8de2d2b0a07dabb0a04476c71d0045ccf555a648

[ "MIT" ]

null

config.py

bukun/gislite

8de2d2b0a07dabb0a04476c71d0045ccf555a648

[ "MIT" ]

9

2019-01-23T17:47:20.000Z

2021-11-22T12:20:02.000Z

from cfg import TILE_SVR from cfg import GIS_BASE

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null

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1

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1

0

1

0

7

8d8a5fac798eb46da71df6936cb070b8d3c212af

6,714

py

Python

te_controller.py

tehnerd/mpls-pce

7c971396a0836bc0be4b4f3d2bfcbc8a0d04f67c

[ "MIT" ]

2

2015-08-17T15:11:42.000Z

2018-05-24T21:52:19.000Z

te_controller.py

tehnerd/mpls-pce

7c971396a0836bc0be4b4f3d2bfcbc8a0d04f67c

[ "MIT" ]

null

te_controller.py

tehnerd/mpls-pce

7c971396a0836bc0be4b4f3d2bfcbc8a0d04f67c

[ "MIT" ]

2

2015-09-27T05:06:16.000Z

2018-10-28T17:48:30.000Z

import socket import mpls_lsp_pb2 import struct class TEController(object): def __init__(self): self.lsp_dict = dict() def ip2int(self, addr): return struct.unpack_from("!I", socket.inet_aton(addr))[0] def int2ip(self, addr): return socket.inet_ntoa(struct.pack("!I", addr)) def handle_pce_message(self, pcc_ip, message): if message[0] == 'state_report': result = self.handle_state_report_od(pcc_ip, message) return result return (None,) def handle_state_report(self, pcc_ip, message): lsp = mpls_lsp_pb2.LSP() first_lsp = 1 for report_object in message[1]: if report_object[0] == 'lsp_obj': if first_lsp != 1: lsp_dict_index = (self.ip2int(pcc_ip[0]),lsp.lsp_obj.plsp_id) new_lsp = mpls_lsp_pb2.LSP() new_lsp.CopyFrom(lsp) self.lsp_dict[lsp_dict_index] = new_lsp else: first_lsp = 0 lsp.Clear() lsp.pcc_ip = pcc_ip[0] lsp.lsp_obj.plsp_id = report_object[1][0] lsp.lsp_obj.delegated = report_object[1][1] lsp.lsp_obj.administrative = report_object[1][4] lsp.lsp_obj.operational = report_object[1][5] if report_object[0] == 'bw': lsp.bandwidth = report_object[1][0] if report_object[0] == 'lspa': lsp.lspa_obj.setup_prio = report_object[1][0] lsp.lspa_obj.hold_prio = report_object[1][1] lsp.lspa_obj.local_protection = report_object[1][2] if report_object[0] == 'ero': if len(report_object[1]) > 0: for ero_node in report_object[1]: ero = lsp.ero.add() ero.loose = ero_node[1] ero.node_ip = self.int2ip(ero_node[2][2]) ero.node_mask = ero_node[2][3] if report_object[0] == 'rro': if len(report_object[1]) > 0: for rro_node in report_object[1]: rro = lsp.rro.add() rro.node_ip = self.int2ip(rro_node[1][2]) rro.node_mask = rro_node[1][3] lsp_dict_index = (self.ip2int(pcc_ip[0]),lsp.lsp_obj.plsp_id) self.lsp_dict[lsp_dict_index] = lsp delegated_lsps = list() for key in self.lsp_dict: lsp = self.lsp_dict[key] if lsp.lsp_obj.delegated: delegated_lsps.append(lsp) print(lsp) if len(delegated_lsps) > 0: resp = list() for lsp in delegated_lsps: resp.extend(self.generate_lsp_upd_msg(lsp)) print(resp) return ('lsp_upd',resp) return (None,) def generate_lsp_upd_msg(self,lsp): upd_msg = list() upd_msg.append(('lsp_obj',(lsp.lsp_obj.plsp_id,lsp.lsp_obj.delegated,0,0, lsp.lsp_obj.administrative, lsp.lsp_obj.operational))) if lsp.ero: ero_list = list() for ero in lsp.ero: ero_list.append((ero.loose,self.ip2int(ero.node_ip), ero.node_mask)) upd_msg.append(('ero',ero_list)) else: upd_msg.append(('ero',((0,0,0),))) upd_msg.append(('lspa',(lsp.lspa_obj.setup_prio,lsp.lspa_obj.hold_prio, lsp.lspa_obj.local_protection))) return upd_msg def handle_state_report_od(self, pcc_ip, message): lsp = mpls_lsp_pb2.LSP() first_lsp = 1 for report_object in message[1]: if report_object[0] == 'lsp_obj': if first_lsp != 1: lsp_dict_index = (self.ip2int(pcc_ip[0]),lsp.lsp_obj.plsp_id) new_lsp = mpls_lsp_pb2.LSP() new_lsp.CopyFrom(lsp) self.lsp_dict[lsp_dict_index] = new_lsp else: first_lsp = 0 lsp.Clear() lsp.pcc_ip = pcc_ip[0] lsp.lsp_obj.plsp_id = report_object[1][0] lsp.lsp_obj.delegated = report_object[1][1] lsp.lsp_obj.operational = report_object[1][3] if report_object[0] == 'bw': lsp.bandwidth = report_object[1][0] if report_object[0] == 'lspa': lsp.lspa_obj.setup_prio = report_object[1][0] lsp.lspa_obj.hold_prio = report_object[1][1] lsp.lspa_obj.local_protection = report_object[1][2] if report_object[0] == 'ero': if len(report_object[1]) > 0: for ero_node in report_object[1]: ero = lsp.ero.add() ero.loose = ero_node[1] ero.node_ip = self.int2ip(ero_node[2][2]) ero.node_mask = ero_node[2][3] if report_object[0] == 'rro': if len(report_object[1]) > 0: for rro_node in report_object[1]: rro = lsp.rro.add() rro.node_ip = self.int2ip(rro_node[1][2]) rro.node_mask = rro_node[1][3] lsp_dict_index = (self.ip2int(pcc_ip[0]),lsp.lsp_obj.plsp_id) self.lsp_dict[lsp_dict_index] = lsp delegated_lsps = list() for key in self.lsp_dict: lsp = self.lsp_dict[key] if lsp.lsp_obj.delegated: delegated_lsps.append(lsp) print(lsp) if len(delegated_lsps) > 0: resp = list() for lsp in delegated_lsps: resp.extend(self.generate_lsp_upd_msg_od(lsp)) print(resp) return ('lsp_upd',resp) return (None,) def generate_lsp_upd_msg_od(self,lsp): upd_msg = list() upd_msg.append(('lsp_obj',(lsp.lsp_obj.plsp_id,lsp.lsp_obj.delegated,0, lsp.lsp_obj.operational,0))) if lsp.ero: ero_list = list() for ero in lsp.ero: ero_list.append((ero.loose,self.ip2int(ero.node_ip), ero.node_mask)) upd_msg.append(('ero',ero_list)) else: upd_msg.append(('ero',((0,0,0),))) upd_msg.append(('lspa',(lsp.lspa_obj.setup_prio,lsp.lspa_obj.hold_prio, lsp.lspa_obj.local_protection))) upd_msg.append(('bw',(lsp.bandwidth,))) return upd_msg

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3.709827

0.092486

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0.093175

0.046744

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0.374144

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null

0

1

0

1

0

null

0

7

a5fb6d75fe7564a16f61cbe7196c81e35159f7a7

407

py

Python

controllers/about.py

bkahlerventer/web2congress

30463ef05a64b95f9ec8a5575e1f45a99986b607

[ "BSD-3-Clause" ]

3

2016-12-29T23:02:35.000Z

2021-07-01T01:10:12.000Z

controllers/about.py

reingart/web2conf

a5e01d9fc2c25b271db7cee528faef58a46e7106

[ "BSD-3-Clause" ]

null

controllers/about.py

reingart/web2conf

a5e01d9fc2c25b271db7cee528faef58a46e7106

[ "BSD-3-Clause" ]

null

# coding: utf8 def index(): return plugin_flatpage() def worldwide(): return plugin_flatpage() def staff(): return plugin_flatpage() def press(): return plugin_flatpage() def events(): return plugin_flatpage() def news(): return plugin_flatpage() def notes(): return plugin_flatpage() def community(): return plugin_flatpage() def connect(): return plugin_flatpage() def photos(): return plugin_flatpage()

31.307692

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0.764128

52

407

5.788462

0.307692

0.398671

0.664452

0.687708

0

0.002755

0.108108

407

12

42

33.916667

0.826446

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0

1

true

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1

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null

1

0

null

0

1

0

1

0

7

938b906f72b23e99311660fc13b4cb6f712d7b78

18,513

py

Python

sdk/python/pulumi_datadog/logs_index.py

pulumi/pulumi-datadog

dbc3e51b438de20aca4207bf894dbaa5a2db4bca

[ "ECL-2.0", "Apache-2.0" ]

10

2019-09-17T20:41:19.000Z

2022-01-07T15:42:07.000Z

sdk/python/pulumi_datadog/logs_index.py

pulumi/pulumi-datadog

dbc3e51b438de20aca4207bf894dbaa5a2db4bca

[ "ECL-2.0", "Apache-2.0" ]

86

2019-07-08T11:47:05.000Z

2022-03-28T21:02:19.000Z

sdk/python/pulumi_datadog/logs_index.py

pulumi/pulumi-datadog

dbc3e51b438de20aca4207bf894dbaa5a2db4bca

[ "ECL-2.0", "Apache-2.0" ]

4

2019-10-05T10:34:15.000Z

2021-08-08T04:14:19.000Z

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. *** # *** 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, overload from . import _utilities from . import outputs from ._inputs import * __all__ = ['LogsIndexArgs', 'LogsIndex'] @pulumi.input_type class LogsIndexArgs: def __init__(__self__, *, filters: pulumi.Input[Sequence[pulumi.Input['LogsIndexFilterArgs']]], name: pulumi.Input[str], daily_limit: Optional[pulumi.Input[int]] = None, disable_daily_limit: Optional[pulumi.Input[bool]] = None, exclusion_filters: Optional[pulumi.Input[Sequence[pulumi.Input['LogsIndexExclusionFilterArgs']]]] = None, retention_days: Optional[pulumi.Input[int]] = None): """ The set of arguments for constructing a LogsIndex resource. :param pulumi.Input[Sequence[pulumi.Input['LogsIndexFilterArgs']]] filters: Logs filter :param pulumi.Input[str] name: The name of the index. :param pulumi.Input[int] daily_limit: The number of log events you can send in this index per day before you are rate-limited. :param pulumi.Input[bool] disable_daily_limit: If true, sets the daily*limit value to null and the index is not limited on a daily basis (any specified daily*limit value in the request is ignored). If false or omitted, the index's current daily_limit is maintained. :param pulumi.Input[Sequence[pulumi.Input['LogsIndexExclusionFilterArgs']]] exclusion_filters: List of exclusion filters. :param pulumi.Input[int] retention_days: The number of days before logs are deleted from this index. """ pulumi.set(__self__, "filters", filters) pulumi.set(__self__, "name", name) if daily_limit is not None: pulumi.set(__self__, "daily_limit", daily_limit) if disable_daily_limit is not None: pulumi.set(__self__, "disable_daily_limit", disable_daily_limit) if exclusion_filters is not None: pulumi.set(__self__, "exclusion_filters", exclusion_filters) if retention_days is not None: pulumi.set(__self__, "retention_days", retention_days) @property @pulumi.getter def filters(self) -> pulumi.Input[Sequence[pulumi.Input['LogsIndexFilterArgs']]]: """ Logs filter """ return pulumi.get(self, "filters") @filters.setter def filters(self, value: pulumi.Input[Sequence[pulumi.Input['LogsIndexFilterArgs']]]): pulumi.set(self, "filters", value) @property @pulumi.getter def name(self) -> pulumi.Input[str]: """ The name of the index. """ return pulumi.get(self, "name") @name.setter def name(self, value: pulumi.Input[str]): pulumi.set(self, "name", value) @property @pulumi.getter(name="dailyLimit") def daily_limit(self) -> Optional[pulumi.Input[int]]: """ The number of log events you can send in this index per day before you are rate-limited. """ return pulumi.get(self, "daily_limit") @daily_limit.setter def daily_limit(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "daily_limit", value) @property @pulumi.getter(name="disableDailyLimit") def disable_daily_limit(self) -> Optional[pulumi.Input[bool]]: """ If true, sets the daily*limit value to null and the index is not limited on a daily basis (any specified daily*limit value in the request is ignored). If false or omitted, the index's current daily_limit is maintained. """ return pulumi.get(self, "disable_daily_limit") @disable_daily_limit.setter def disable_daily_limit(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "disable_daily_limit", value) @property @pulumi.getter(name="exclusionFilters") def exclusion_filters(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['LogsIndexExclusionFilterArgs']]]]: """ List of exclusion filters. """ return pulumi.get(self, "exclusion_filters") @exclusion_filters.setter def exclusion_filters(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['LogsIndexExclusionFilterArgs']]]]): pulumi.set(self, "exclusion_filters", value) @property @pulumi.getter(name="retentionDays") def retention_days(self) -> Optional[pulumi.Input[int]]: """ The number of days before logs are deleted from this index. """ return pulumi.get(self, "retention_days") @retention_days.setter def retention_days(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "retention_days", value) @pulumi.input_type class _LogsIndexState: def __init__(__self__, *, daily_limit: Optional[pulumi.Input[int]] = None, disable_daily_limit: Optional[pulumi.Input[bool]] = None, exclusion_filters: Optional[pulumi.Input[Sequence[pulumi.Input['LogsIndexExclusionFilterArgs']]]] = None, filters: Optional[pulumi.Input[Sequence[pulumi.Input['LogsIndexFilterArgs']]]] = None, name: Optional[pulumi.Input[str]] = None, retention_days: Optional[pulumi.Input[int]] = None): """ Input properties used for looking up and filtering LogsIndex resources. :param pulumi.Input[int] daily_limit: The number of log events you can send in this index per day before you are rate-limited. :param pulumi.Input[bool] disable_daily_limit: If true, sets the daily*limit value to null and the index is not limited on a daily basis (any specified daily*limit value in the request is ignored). If false or omitted, the index's current daily_limit is maintained. :param pulumi.Input[Sequence[pulumi.Input['LogsIndexExclusionFilterArgs']]] exclusion_filters: List of exclusion filters. :param pulumi.Input[Sequence[pulumi.Input['LogsIndexFilterArgs']]] filters: Logs filter :param pulumi.Input[str] name: The name of the index. :param pulumi.Input[int] retention_days: The number of days before logs are deleted from this index. """ if daily_limit is not None: pulumi.set(__self__, "daily_limit", daily_limit) if disable_daily_limit is not None: pulumi.set(__self__, "disable_daily_limit", disable_daily_limit) if exclusion_filters is not None: pulumi.set(__self__, "exclusion_filters", exclusion_filters) if filters is not None: pulumi.set(__self__, "filters", filters) if name is not None: pulumi.set(__self__, "name", name) if retention_days is not None: pulumi.set(__self__, "retention_days", retention_days) @property @pulumi.getter(name="dailyLimit") def daily_limit(self) -> Optional[pulumi.Input[int]]: """ The number of log events you can send in this index per day before you are rate-limited. """ return pulumi.get(self, "daily_limit") @daily_limit.setter def daily_limit(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "daily_limit", value) @property @pulumi.getter(name="disableDailyLimit") def disable_daily_limit(self) -> Optional[pulumi.Input[bool]]: """ If true, sets the daily*limit value to null and the index is not limited on a daily basis (any specified daily*limit value in the request is ignored). If false or omitted, the index's current daily_limit is maintained. """ return pulumi.get(self, "disable_daily_limit") @disable_daily_limit.setter def disable_daily_limit(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "disable_daily_limit", value) @property @pulumi.getter(name="exclusionFilters") def exclusion_filters(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['LogsIndexExclusionFilterArgs']]]]: """ List of exclusion filters. """ return pulumi.get(self, "exclusion_filters") @exclusion_filters.setter def exclusion_filters(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['LogsIndexExclusionFilterArgs']]]]): pulumi.set(self, "exclusion_filters", value) @property @pulumi.getter def filters(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['LogsIndexFilterArgs']]]]: """ Logs filter """ return pulumi.get(self, "filters") @filters.setter def filters(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['LogsIndexFilterArgs']]]]): pulumi.set(self, "filters", value) @property @pulumi.getter def name(self) -> Optional[pulumi.Input[str]]: """ The name of the index. """ return pulumi.get(self, "name") @name.setter def name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "name", value) @property @pulumi.getter(name="retentionDays") def retention_days(self) -> Optional[pulumi.Input[int]]: """ The number of days before logs are deleted from this index. """ return pulumi.get(self, "retention_days") @retention_days.setter def retention_days(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "retention_days", value) class LogsIndex(pulumi.CustomResource): @overload def __init__(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, daily_limit: Optional[pulumi.Input[int]] = None, disable_daily_limit: Optional[pulumi.Input[bool]] = None, exclusion_filters: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['LogsIndexExclusionFilterArgs']]]]] = None, filters: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['LogsIndexFilterArgs']]]]] = None, name: Optional[pulumi.Input[str]] = None, retention_days: Optional[pulumi.Input[int]] = None, __props__=None): """ ## Import ```sh $ pulumi import datadog:index/logsIndex:LogsIndex name> <indexName> ``` :param str resource_name: The name of the resource. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[int] daily_limit: The number of log events you can send in this index per day before you are rate-limited. :param pulumi.Input[bool] disable_daily_limit: If true, sets the daily*limit value to null and the index is not limited on a daily basis (any specified daily*limit value in the request is ignored). If false or omitted, the index's current daily_limit is maintained. :param pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['LogsIndexExclusionFilterArgs']]]] exclusion_filters: List of exclusion filters. :param pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['LogsIndexFilterArgs']]]] filters: Logs filter :param pulumi.Input[str] name: The name of the index. :param pulumi.Input[int] retention_days: The number of days before logs are deleted from this index. """ ... @overload def __init__(__self__, resource_name: str, args: LogsIndexArgs, opts: Optional[pulumi.ResourceOptions] = None): """ ## Import ```sh $ pulumi import datadog:index/logsIndex:LogsIndex name> <indexName> ``` :param str resource_name: The name of the resource. :param LogsIndexArgs args: The arguments to use to populate this resource's properties. :param pulumi.ResourceOptions opts: Options for the resource. """ ... def __init__(__self__, resource_name: str, *args, **kwargs): resource_args, opts = _utilities.get_resource_args_opts(LogsIndexArgs, pulumi.ResourceOptions, *args, **kwargs) if resource_args is not None: __self__._internal_init(resource_name, opts, **resource_args.__dict__) else: __self__._internal_init(resource_name, *args, **kwargs) def _internal_init(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, daily_limit: Optional[pulumi.Input[int]] = None, disable_daily_limit: Optional[pulumi.Input[bool]] = None, exclusion_filters: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['LogsIndexExclusionFilterArgs']]]]] = None, filters: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['LogsIndexFilterArgs']]]]] = None, name: Optional[pulumi.Input[str]] = None, retention_days: Optional[pulumi.Input[int]] = None, __props__=None): if opts is None: opts = pulumi.ResourceOptions() if not isinstance(opts, pulumi.ResourceOptions): raise TypeError('Expected resource options to be a ResourceOptions instance') if opts.version is None: opts.version = _utilities.get_version() if opts.id is None: if __props__ is not None: raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource') __props__ = LogsIndexArgs.__new__(LogsIndexArgs) __props__.__dict__["daily_limit"] = daily_limit __props__.__dict__["disable_daily_limit"] = disable_daily_limit __props__.__dict__["exclusion_filters"] = exclusion_filters if filters is None and not opts.urn: raise TypeError("Missing required property 'filters'") __props__.__dict__["filters"] = filters if name is None and not opts.urn: raise TypeError("Missing required property 'name'") __props__.__dict__["name"] = name __props__.__dict__["retention_days"] = retention_days super(LogsIndex, __self__).__init__( 'datadog:index/logsIndex:LogsIndex', resource_name, __props__, opts) @staticmethod def get(resource_name: str, id: pulumi.Input[str], opts: Optional[pulumi.ResourceOptions] = None, daily_limit: Optional[pulumi.Input[int]] = None, disable_daily_limit: Optional[pulumi.Input[bool]] = None, exclusion_filters: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['LogsIndexExclusionFilterArgs']]]]] = None, filters: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['LogsIndexFilterArgs']]]]] = None, name: Optional[pulumi.Input[str]] = None, retention_days: Optional[pulumi.Input[int]] = None) -> 'LogsIndex': """ Get an existing LogsIndex resource's state with the given name, id, and optional extra properties used to qualify the lookup. :param str resource_name: The unique name of the resulting resource. :param pulumi.Input[str] id: The unique provider ID of the resource to lookup. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[int] daily_limit: The number of log events you can send in this index per day before you are rate-limited. :param pulumi.Input[bool] disable_daily_limit: If true, sets the daily*limit value to null and the index is not limited on a daily basis (any specified daily*limit value in the request is ignored). If false or omitted, the index's current daily_limit is maintained. :param pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['LogsIndexExclusionFilterArgs']]]] exclusion_filters: List of exclusion filters. :param pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['LogsIndexFilterArgs']]]] filters: Logs filter :param pulumi.Input[str] name: The name of the index. :param pulumi.Input[int] retention_days: The number of days before logs are deleted from this index. """ opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id)) __props__ = _LogsIndexState.__new__(_LogsIndexState) __props__.__dict__["daily_limit"] = daily_limit __props__.__dict__["disable_daily_limit"] = disable_daily_limit __props__.__dict__["exclusion_filters"] = exclusion_filters __props__.__dict__["filters"] = filters __props__.__dict__["name"] = name __props__.__dict__["retention_days"] = retention_days return LogsIndex(resource_name, opts=opts, __props__=__props__) @property @pulumi.getter(name="dailyLimit") def daily_limit(self) -> pulumi.Output[Optional[int]]: """ The number of log events you can send in this index per day before you are rate-limited. """ return pulumi.get(self, "daily_limit") @property @pulumi.getter(name="disableDailyLimit") def disable_daily_limit(self) -> pulumi.Output[bool]: """ If true, sets the daily*limit value to null and the index is not limited on a daily basis (any specified daily*limit value in the request is ignored). If false or omitted, the index's current daily_limit is maintained. """ return pulumi.get(self, "disable_daily_limit") @property @pulumi.getter(name="exclusionFilters") def exclusion_filters(self) -> pulumi.Output[Optional[Sequence['outputs.LogsIndexExclusionFilter']]]: """ List of exclusion filters. """ return pulumi.get(self, "exclusion_filters") @property @pulumi.getter def filters(self) -> pulumi.Output[Sequence['outputs.LogsIndexFilter']]: """ Logs filter """ return pulumi.get(self, "filters") @property @pulumi.getter def name(self) -> pulumi.Output[str]: """ The name of the index. """ return pulumi.get(self, "name") @property @pulumi.getter(name="retentionDays") def retention_days(self) -> pulumi.Output[int]: """ The number of days before logs are deleted from this index. """ return pulumi.get(self, "retention_days")

46.868354

273

0.662994

2,192

18,513

5.393248

0.078923

0.100491

0.077144

0.054982

0.85214

0.830993

0.82228

0.801641

0.792421

0.773473

0

0.000071

0.233836

18,513

394

274

46.98731

0.833404

0.299195

0

0.723404

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0

0.130431

0.028032

0

1

0.157447

false

0.004255

0.029787

0

0.280851

0

null

0

1

0

1

0

null

0

8

93943a63a164097960c10877bba7803ba20448f3

133

py

Python

sktime/classifiers/dictionary_based/__init__.py

Mo-Saif/sktime

f3c71977c113d986276fca2bdedf70faaa33f040

[ "BSD-3-Clause" ]

1

2019-09-29T07:11:33.000Z

sktime/classifiers/dictionary_based/__init__.py

ClaudiaSanches/sktime

63e7839e80ca6d5fe5fc4f33389ec3bcacd8aa59

[ "BSD-3-Clause" ]

null

sktime/classifiers/dictionary_based/__init__.py

ClaudiaSanches/sktime

63e7839e80ca6d5fe5fc4f33389ec3bcacd8aa59

[ "BSD-3-Clause" ]

1

2019-05-08T10:42:20.000Z

from sktime.classifiers.dictionary_based.boss import BOSSEnsemble from sktime.classifiers.dictionary_based.boss import BOSSIndividual

66.5

67

0.902256

16

133

7.375

0.5625

0.169492

0.355932

0.525424

0.779661

0

0.052632

133

2

67

66.5

0.936508

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

1

0

1

0

null

0

1

0

1

0

1

0

9

93bdd69e8a2a869640a3251a0f88cc1700008e6b

133

py

Python

ejercicios_basicos/constantes/test_constantes.py

JuanDuran85/ejemplos_python

47aa49c65384ab89654f362f3da6cd2b0ef386e5

[ "Apache-2.0" ]

null

ejercicios_basicos/constantes/test_constantes.py

JuanDuran85/ejemplos_python

47aa49c65384ab89654f362f3da6cd2b0ef386e5

[ "Apache-2.0" ]

null

ejercicios_basicos/constantes/test_constantes.py

JuanDuran85/ejemplos_python

47aa49c65384ab89654f362f3da6cd2b0ef386e5

[ "Apache-2.0" ]

null

from constantes import NUEVA_CONSTANTE from constantes import Matematica as Mate_Const print(Mate_Const.PI) print(NUEVA_CONSTANTE)

19

47

0.857143

19

133

5.789474

0.578947

0.254545

0.363636

0

0.105263

133

6

48

22.166667

0.92437

0

1

0

true

0

0.5

0

0.5

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

93df34eada0cf35cf8f3add5b0fe76aa24e7d377

166

py

Python

schematic/schemas/__init__.py

linglp/schematic

fd0308c43783ac8e367e8a5be0cc6e4bfbc44b29

[ "MIT" ]

8

2020-11-06T23:38:06.000Z

2022-02-03T11:05:25.000Z

schematic/schemas/__init__.py

linglp/schematic

fd0308c43783ac8e367e8a5be0cc6e4bfbc44b29

[ "MIT" ]

326

2020-09-15T20:52:59.000Z

2022-03-31T23:20:35.000Z

schematic/schemas/__init__.py

linglp/schematic

fd0308c43783ac8e367e8a5be0cc6e4bfbc44b29

[ "MIT" ]

15

2020-09-16T23:12:09.000Z

2022-03-14T23:05:46.000Z

from schematic.schemas.explorer import SchemaExplorer from schematic.schemas.generator import SchemaGenerator from schematic.schemas.validator import SchemaValidator

41.5

55

0.891566

18

166

8.222222

0.555556

0.263514

0.405405

0

0.072289

166

3

56

55.333333

0.961039

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

9e0e98e458609dfa7feb5f06525697be13f20331

84

py

Python

KeyMojiAPI/__init__.py

Droidtown/KeyMojiAPI

c870eda9672c5a466cd705e97ec4edba80a83169

[ "MIT" ]

8

2021-03-18T01:19:41.000Z

2022-03-03T17:03:51.000Z

KeyMojiAPI/__init__.py

Droidtown/KeyMojiAPI

c870eda9672c5a466cd705e97ec4edba80a83169

[ "MIT" ]

null

KeyMojiAPI/__init__.py

Droidtown/KeyMojiAPI

c870eda9672c5a466cd705e97ec4edba80a83169

[ "MIT" ]

4

2022-02-12T03:11:43.000Z

2022-03-11T08:13:47.000Z

try: from KeyMojiAPI import KeyMoji except: from .KeyMojiAPI import KeyMoji

16.8

35

0.75

10

84

6.3

0.6

0.444444

0.634921

0.857143

0

0.214286

84

4

36

21

0.954545

0

1

0

true

0

0.5

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

1

0

7

f57fca960e4d356373fd745a6f607f0a4b3b00f1

5,294

py

Python

test/test_koldate.py

danheath/pykol-lib

bdc9aa8dbae64ead07e7dbc36f9d6ba802f65ddc

[ "BSD-3-Clause" ]

6

2019-06-11T19:25:32.000Z

2022-01-21T17:05:01.000Z

test/test_koldate.py

danheath/pykol-lib

bdc9aa8dbae64ead07e7dbc36f9d6ba802f65ddc

[ "BSD-3-Clause" ]

8

2019-06-17T11:41:14.000Z

2019-08-07T17:28:50.000Z

test/test_koldate.py

python-kol/pykollib

bdc9aa8dbae64ead07e7dbc36f9d6ba802f65ddc

[ "BSD-3-Clause" ]

9

2019-06-09T22:23:06.000Z

2021-07-10T00:49:00.000Z

from unittest import TestCase from libkol.koldate import koldate class KoldateTestCase(TestCase): def test_ronald_phase(self): self.assertEqual(koldate(52, 2, 0).ronald_phase, 0) self.assertEqual(koldate(52, 2, 1).ronald_phase, 1) self.assertEqual(koldate(52, 2, 2).ronald_phase, 2) self.assertEqual(koldate(52, 2, 3).ronald_phase, 3) self.assertEqual(koldate(52, 2, 4).ronald_phase, 4) self.assertEqual(koldate(52, 2, 5).ronald_phase, 5) self.assertEqual(koldate(52, 2, 6).ronald_phase, 6) self.assertEqual(koldate(52, 2, 7).ronald_phase, 7) def test_ronald_light(self): self.assertEqual(koldate(52, 2, 0).ronald_light, 0) self.assertEqual(koldate(52, 2, 1).ronald_light, 1) self.assertEqual(koldate(52, 2, 2).ronald_light, 2) self.assertEqual(koldate(52, 2, 3).ronald_light, 3) self.assertEqual(koldate(52, 2, 4).ronald_light, 4) self.assertEqual(koldate(52, 2, 5).ronald_light, 3) self.assertEqual(koldate(52, 2, 6).ronald_light, 2) self.assertEqual(koldate(52, 2, 7).ronald_light, 1) def test_grimace_phase(self): self.assertEqual(koldate(52, 2, 0).grimace_phase, 0) self.assertEqual(koldate(52, 2, 1).grimace_phase, 0) self.assertEqual(koldate(52, 2, 2).grimace_phase, 1) self.assertEqual(koldate(52, 2, 3).grimace_phase, 1) self.assertEqual(koldate(52, 2, 4).grimace_phase, 2) self.assertEqual(koldate(52, 2, 5).grimace_phase, 2) self.assertEqual(koldate(52, 2, 6).grimace_phase, 3) self.assertEqual(koldate(52, 2, 7).grimace_phase, 3) self.assertEqual(koldate(52, 3, 0).grimace_phase, 4) self.assertEqual(koldate(52, 3, 1).grimace_phase, 4) self.assertEqual(koldate(52, 3, 2).grimace_phase, 5) self.assertEqual(koldate(52, 3, 3).grimace_phase, 5) self.assertEqual(koldate(52, 3, 4).grimace_phase, 6) self.assertEqual(koldate(52, 3, 5).grimace_phase, 6) self.assertEqual(koldate(52, 3, 6).grimace_phase, 7) self.assertEqual(koldate(52, 3, 7).grimace_phase, 7) def test_grimace_light(self): self.assertEqual(koldate(52, 2, 0).grimace_light, 0) self.assertEqual(koldate(52, 2, 1).grimace_light, 0) self.assertEqual(koldate(52, 2, 2).grimace_light, 1) self.assertEqual(koldate(52, 2, 3).grimace_light, 1) self.assertEqual(koldate(52, 2, 4).grimace_light, 2) self.assertEqual(koldate(52, 2, 5).grimace_light, 2) self.assertEqual(koldate(52, 2, 6).grimace_light, 3) self.assertEqual(koldate(52, 2, 7).grimace_light, 3) self.assertEqual(koldate(52, 3, 0).grimace_light, 4) self.assertEqual(koldate(52, 3, 1).grimace_light, 4) self.assertEqual(koldate(52, 3, 2).grimace_light, 3) self.assertEqual(koldate(52, 3, 3).grimace_light, 3) self.assertEqual(koldate(52, 3, 4).grimace_light, 2) self.assertEqual(koldate(52, 3, 5).grimace_light, 2) self.assertEqual(koldate(52, 3, 6).grimace_light, 1) self.assertEqual(koldate(52, 3, 7).grimace_light, 1) def test_hamburglar_phase(self): self.assertEqual(koldate(52, 2, 0).hamburglar_phase, 7) self.assertEqual(koldate(52, 2, 1).hamburglar_phase, 9) self.assertEqual(koldate(52, 2, 2).hamburglar_phase, 0) self.assertEqual(koldate(52, 2, 3).hamburglar_phase, 2) self.assertEqual(koldate(52, 2, 4).hamburglar_phase, 4) self.assertEqual(koldate(52, 2, 5).hamburglar_phase, 6) self.assertEqual(koldate(52, 2, 6).hamburglar_phase, 8) self.assertEqual(koldate(52, 2, 7).hamburglar_phase, 10) self.assertEqual(koldate(52, 3, 0).hamburglar_phase, 1) self.assertEqual(koldate(52, 3, 1).hamburglar_phase, 3) self.assertEqual(koldate(52, 3, 2).hamburglar_phase, 5) def test_hamburglar_light(self): self.assertEqual(koldate(52, 2, 0).hamburglar_light, 0) self.assertEqual(koldate(52, 2, 1).hamburglar_light, 1) self.assertEqual(koldate(52, 2, 2).hamburglar_light, -1) self.assertEqual(koldate(52, 2, 3).hamburglar_light, 0) self.assertEqual(koldate(52, 2, 4).hamburglar_light, 1) self.assertEqual(koldate(52, 2, 5).hamburglar_light, 0) self.assertEqual(koldate(52, 2, 6).hamburglar_light, 1) self.assertEqual(koldate(52, 2, 7).hamburglar_light, 2) self.assertEqual(koldate(52, 3, 0).hamburglar_light, -1) self.assertEqual(koldate(52, 3, 1).hamburglar_light, 0) self.assertEqual(koldate(52, 3, 2).hamburglar_light, 0) def test_moonlight(self): self.assertEqual(koldate(52, 2, 0).moonlight, 0) self.assertEqual(koldate(52, 2, 1).moonlight, 2) self.assertEqual(koldate(52, 2, 2).moonlight, 2) self.assertEqual(koldate(52, 2, 3).moonlight, 4) self.assertEqual(koldate(52, 2, 4).moonlight, 7) self.assertEqual(koldate(52, 2, 5).moonlight, 5) self.assertEqual(koldate(52, 2, 6).moonlight, 6) self.assertEqual(koldate(52, 2, 7).moonlight, 6) self.assertEqual(koldate(52, 3, 0).moonlight, 3) self.assertEqual(koldate(52, 3, 1).moonlight, 5) self.assertEqual(koldate(52, 3, 2).moonlight, 5)

52.94

64

0.662259

764

5,294

4.480366

0.039267

0.354952

0.520596

0.567923

0.915571

0.857435

0.621385

0

0.09526

0.194938

5,294

99

65

53.474747

0.707884

0

0.89011

1

0.076923

false

0

0.021978

0

0.10989

0

null

1

0

null

0

1

0

7

f5a58fadfd264bfcb55f42d9fbb515287572ba2c

122

py

Python

discord/errors.py

kuzaku-developers/disnake

61cc1ad4c2bafd39726a1447c85f7e469e41af10

[ "MIT" ]

null

discord/errors.py

kuzaku-developers/disnake

61cc1ad4c2bafd39726a1447c85f7e469e41af10

[ "MIT" ]

null

discord/errors.py

kuzaku-developers/disnake

61cc1ad4c2bafd39726a1447c85f7e469e41af10

[ "MIT" ]

null

from disnake.errors import * from disnake.errors import __dict__ as __original_dict__ locals().update(__original_dict__)

24.4

56

0.836066

16

122

5.5

0.5625

0.25

0.386364

0.522727

0

0.098361

122

4

57

30.5

0.8

0

1

0

true

0

0.666667

0

0.666667

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

8

f5a600b8ad3dfb3f42defdf59662c634c2690d8b

1,177

py

Python

classifier/state_script.py

josephmaa/pyuoi

f546900791c3c2176e5ac2ac6c553bae065a3127

[ "BSD-3-Clause-LBNL" ]

null

classifier/state_script.py

josephmaa/pyuoi

f546900791c3c2176e5ac2ac6c553bae065a3127

[ "BSD-3-Clause-LBNL" ]

2

2022-03-01T22:32:20.000Z

2022-03-08T22:31:46.000Z

classifier/state_script.py

josephmaa/pyuoi

f546900791c3c2176e5ac2ac6c553bae065a3127

[ "BSD-3-Clause-LBNL" ]

null

import subprocess import sys classifier = "classifier/rat7m_classifier.py" for seed in range(1, 21): print(f"Running seed: {seed}") # Call the classifier with a training seed and a model seed up through 20. subprocess.call(["python", classifier, "--input_files", "/Users/josephgmaa/pyuoi/pyuoi/data/features/PCs/PCs-mavg-velocity_relative.netcdf", "--column_names", "PCA_mavg_velocity_relative_0", "PCA_mavg_velocity_relative_1", "PCA_mavg_velocity_relative_2" "PCA_mavg_velocity_relative_3", "PCA_mavg_velocity_relative_4", "--training_seed", str(seed)], stdout=sys.stdout, stderr=subprocess.STDOUT) subprocess.call(["python", classifier, "--input_files", "/Users/josephgmaa/pyuoi/pyuoi/data/features/PCs/PCs-mavg-velocity_relative.netcdf", "--column_names", "PCA_mavg_velocity_relative_0", "PCA_mavg_velocity_relative_1", "PCA_mavg_velocity_relative_2" "PCA_mavg_velocity_relative_3", "PCA_mavg_velocity_relative_4", "--model_seed", str(seed)], stdout=sys.stdout, stderr=subprocess.STDOUT)

58.85

178

0.676296

144

1,177

5.1875

0.333333

0.192771

0.321285

0.307898

0.771084

0.64257

0

0.017131

0.206457

1,177

19

179

61.947368

0.782655

0.061172

0

0.533333

0

0.133333

0.530372

0.427924

0

1

0

false

0

0.133333

0

0.133333

0.066667

0

null

0

1

0

1

0

1

null

0

8

5fd813cb0377bdab626c5e5a939464298b9a6653

5,206

py

Python

dvdrenal_task/dvdrenal_app/models.py

mohamedashrafamin/Training_one

11748fdde85cdc9083e2b0bde7519b51a7acfa62

[ "MIT" ]

null

dvdrenal_task/dvdrenal_app/models.py

mohamedashrafamin/Training_one

11748fdde85cdc9083e2b0bde7519b51a7acfa62

[ "MIT" ]

2

2019-01-22T10:53:42.000Z

2019-01-31T08:02:48.000Z

dvdrenal_task/dvdrenal_app/models.py

mohamedashrafamin/Training_one

11748fdde85cdc9083e2b0bde7519b51a7acfa62

[ "MIT" ]

13

2019-01-22T10:37:42.000Z

2019-01-25T13:30:43.000Z

from django.db import models # Create your models here. class actor_name_v(models.Model): Actor_name = models.CharField(max_length=100) class Meta: db_table = "actor_name_v" def __str__(self): return str(self.Actor_name) class actors_v(models.Model): actor_id = models.IntegerField first_name = models.CharField(max_length=100) last_name = models.CharField(max_length=100) class Meta: db_table = "actors_v" def __str__(self): return str(self.first_name) class add_colom_v(models.Model): actor_id = models.IntegerField first_name = models.CharField(max_length=100) last_name = models.CharField(max_length=100) last_update = models.CharField(max_length=100) middle_name = models.CharField(max_length=100) class Meta: db_table = "add_colom_v" def __str__(self): return str(self.first_name) class all_actors_film_v(models.Model): actor_id = models.IntegerField first_name = models.CharField(max_length=100) last_name = models.CharField(max_length=100) class Meta: db_table = "all_actors_film_v" def __str__(self): return str(self.first_name) class all_end_gen_v(models.Model): actor_id = models.IntegerField first_name = models.CharField(max_length=100) last_name = models.CharField(max_length=100) class Meta: db_table = "all_end_gen_v" def __str__(self): return str(self.first_name) class all_end_li_v(models.Model): actor_id = models.IntegerField first_name = models.CharField(max_length=100) last_name = models.CharField(max_length=100) class Meta: db_table = "all_end_li_v" def __str__(self): return str(self.first_name) class count_last_least_v(models.Model): last_name = models.CharField(max_length=100) Count = models.IntegerField class Meta: db_table = "count_last_least_v" def __str__(self): return str(self.last_name) class count_last_v(models.Model): Count = models.IntegerField last_name = models.CharField(max_length=100) class Meta: db_table = "count_last_v" def __str__(self): return str(self.last_name) class country_id_v(models.Model): country_id = models.IntegerField country = models.CharField(max_length=100) class Meta: db_table = "country_id_v" def __str__(self): return str(self.country) class customer_pay_v(models.Model): first_name = models.CharField(max_length=100) last_name = models.CharField(max_length=100) TOTAL = models.DecimalField class Meta: db_table = "customer_pay_v" def __str__(self): return str(self.first_name) class email_v(models.Model): first_name = models.CharField(max_length=100) last_name = models.CharField(max_length=100) email = models.CharField(max_length=100) class Meta: db_table = "email_v" def __str__(self): return str(self.first_name) class f_l_add_v(models.Model): first_name = models.CharField(max_length=100) last_name = models.CharField(max_length=100) address = models.CharField(max_length=100) class Meta: db_table = "f_l_add_v" def __str__(self): return str(self.first_name) class film_number_v(models.Model): title = models.CharField(max_length=100) TOTAL = models.IntegerField class Meta: db_table = "film_number_v" def __str__(self): return str(self.title) class frequently_v(models.Model): title = models.CharField(max_length=100) Count = models.IntegerField class Meta: db_table = "frequently_v" def __str__(self): return str(self.title) class joe_data_v(models.Model): actor_id = models.IntegerField first_name = models.CharField(max_length=100) last_name = models.CharField(max_length=100) class Meta: db_table = "joe_data_v" def __str__(self): return str(self.first_name) class music_kris_v(models.Model): title = models.CharField(max_length=100) class Meta: db_table = "music_kris_v" def __str__(self): return str(self.title) class store_business_v(models.Model): store_id = models.IntegerField() dollars = models.FloatField() class Meta: db_table = "store_business_v" def __str__(self): return str(self.store_id) class store_id_v(models.Model): store_id = models.IntegerField city = models.CharField(max_length=100) country = models.CharField(max_length=100) class Meta: db_table = "store_id_v" def __str__(self): return str(self.city) class top_five_v(models.Model): Gross = models.FloatField Top_Five = models.CharField(max_length=100) class Meta: db_table = "top_five_v" def __str__(self): return str(self.Top_Five) class total_amount_rung_v(models.Model): TOTAL = models.FloatField first_name = models.CharField(max_length=100) last_name = models.CharField(max_length=100) class Meta: db_table = "total_amount_rung_v" def __str__(self): return str(self.first_name)

22.247863

50

0.685555

720

5,206

4.581944

0.090278

0.084874

0.185511

0.247348

0.797211

0.772962

0.759018

0.704456

0.688694

0.571992

0

0.025123

0.220131

5,206

233

51

22.343348

0.787438

0.00461

0

0.598684

0

0.047683

0

1

0.131579

false

0

0.006579

0.131579

0.868421

0

null

0

1

0

1

0

null

0

1

0

7

5fe9fabd2c00132368958c70e95334a6967603ce

18,252

py

Python

fixtures/vdns_fixture.py

rombie/contrail-test

a68c71d6f282142501a7e2e889bbb232fdd82dc3

[ "Apache-2.0" ]

null

fixtures/vdns_fixture.py

rombie/contrail-test

a68c71d6f282142501a7e2e889bbb232fdd82dc3

[ "Apache-2.0" ]

null

fixtures/vdns_fixture.py

rombie/contrail-test

a68c71d6f282142501a7e2e889bbb232fdd82dc3

[ "Apache-2.0" ]

null

import fixtures from vnc_api.vnc_api import NoIdError from vnc_api.gen.cfixture import ContrailFixture from vnc_api.gen.resource_test import VirtualDnsTestFixtureGen from vnc_api.gen.resource_test import VirtualDnsRecordTestFixtureGen from util import retry class VdnsFixture(ContrailFixture): def __init__(self, inputs, connections, vdns_name, dns_data): self.logger = inputs.logger self.vnc_lib = connections.vnc_lib self.api_s_inspect = connections.api_server_inspect self.cn_inspect = connections.cn_inspect self.inputs = inputs self.vdns_name = vdns_name self.dns_data = dns_data self.obj = None def setUp(self): self.logger.debug("Creating VDNS : %s", self.vdns_name) super(VdnsFixture, self).setUp() self.vdns_fix = self.useFixture(VirtualDnsTestFixtureGen( self.vnc_lib, virtual_DNS_name=self.vdns_name, virtual_DNS_data=self.dns_data, auto_prop_val=True)) self.obj = self.vdns_fix.getObj() self.vdns_fq_name = self.obj.get_fq_name_str() def cleanUp(self): self.logger.debug("Deleting VDNS Entry: %s", self.vdns_name) super(VdnsFixture, self).cleanUp() result, msg = self.verify_on_cleanup() assert result, msg def verify_on_setup(self): retval = True errmsg = '' self.logger.info("in verify_on_setup") try: vdns = self.vnc_lib.virtual_DNS_read( fq_name=self.obj.get_fq_name()) self.logger.debug("VDNS: %s created succesfully", self.obj.get_fq_name()) except NoIdError: errmsg = errmsg + \ "\n VDNS: %s not created." % self.obj.get_fq_name() self.logger.warn(errmsg) return False, errmsg self.logger.info("Verify VDNS entry is shown in control node") retval1 = self.verify_vdns_in_control_node() if not retval1: retval = True and False errmsg = errmsg + "\n VDNS server " + \ self.obj.get_fq_name() + \ " info not found not found in control node" self.logger.error("VDNS info not found not found in control node") self.logger.info("Verify VDNS entry is shown in the API server") retval2 = self.verify_vdns_in_api_server() if not retval2: retval = True and False errmsg = errmsg + "\n VDNS server " + \ self.obj.get_fq_name() + \ " info not found not found in API server" self.logger.error("VDNS info not found not found in API server") if not retval: return False, errmsg self.logger.info("out of verify_on_setup") return True, None @retry(delay=3, tries=5) def verify_vdns_in_control_node(self): ''' verify VDNS data in control node''' self.logger.info("Inside verify_vdns_in_control_node") result = True msg = '' for cn in self.inputs.bgp_ips: try: cn_s_dns = self.cn_inspect[cn].get_cn_vdns( vdns=str(self.obj.name)) if self.obj.get_fq_name_str() not in cn_s_dns['node_name']: result = result and False msg = msg + \ '\nvdns name info not matching with control name data' act_cn_vdns_data = cn_s_dns['obj_info'][ 'data']['virtual-DNS-data'] print act_cn_vdns_data exp_vdns_data = self.obj.get_virtual_DNS_data() if act_cn_vdns_data: if exp_vdns_data.__dict__['domain_name'] != act_cn_vdns_data['domain-name']: result = result and False msg = msg + \ '\nvdns domain name is not matching with control node data' if str(exp_vdns_data.__dict__['default_ttl_seconds']) != act_cn_vdns_data['default-ttl-seconds']: result = result and False msg = msg + \ '\nvdns ttl value is not matching with control node data' if exp_vdns_data.__dict__['record_order'] != act_cn_vdns_data['record-order']: result = result and False msg = msg + \ '\nvdns record order value is not matching with control node data' if exp_vdns_data.__dict__['next_virtual_DNS'] != act_cn_vdns_data['next-virtual-DNS']: result = result and False msg = msg + \ '\nvdns next virtual DNS data is not matching with control node data' except Exception as e: # Return false if we get an key error and for retry return False if msg != '': self.logger.info( "VDNS info is not matching with control node data\n %s:", msg) self.logger.info("Outside verify_vdns_in_control_node") return result # end verify_dns_in_control_node @retry(delay=3, tries=5) def verify_vdns_in_api_server(self): ''' verify VDNS data in API server ''' self.logger.info("Inside verify_vdns_in_api_server") result = True api_s_dns = self.api_s_inspect.get_cs_dns( vdns_name=str(self.obj.name), refresh=True) print api_s_dns msg = '' try: if self.obj.get_fq_name() != api_s_dns['virtual-DNS']['fq_name']: result = result and False msg = msg + \ '\n fq name data is not matching with api server data' if self.obj.uuid != api_s_dns['virtual-DNS']['uuid']: result = result and False msg = msg + '\n UUID is is not matching with api server data' api_vdns_data = api_s_dns['virtual-DNS']['virtual_DNS_data'] exp_vdns_data = self.obj.get_virtual_DNS_data() for data in api_vdns_data: if str(exp_vdns_data.__dict__[data]) != str(api_vdns_data.get(data)): result = result and False msg = msg + '\nvdns ' + data + \ ' is not matching with api server data' except Exception as e: # Return false if we get an key error and for retry return False if msg != '': self.logger.info( "VDNS info is not matching with API server\n %s:", msg) self.logger.info("Outside verify_vdns_in_api_server") return result # end verify_vdns_in_api_server @retry(delay=2, tries=5) def verify_vdns_not_in_api_server(self): """Validate VDNS information in API-Server.""" if self.api_s_inspect.get_cs_dns(vdns_name=str(self.obj.name), refresh=True) is not None: errmsg = "VDNS information %s still found in the API Server" % self.obj.name self.logger.warn(errmsg) return False else: self.logger.info( "VDNS information %s removed from the API Server", self.obj.name) return True @retry(delay=2, tries=5) def verify_vdns_not_in_control_node(self): for cn in self.inputs.bgp_ips: cn_s_dns = self.cn_inspect[cn].get_cn_vdns( vdns=str(self.obj.name)) if cn_s_dns: errmsg = "VDNS information %s still found in the Control node" % self.obj.name self.logger.warn(errmsg) return False else: self.logger.info( "VDNS information %s removed in the Control node", self.obj.name) return True def verify_on_cleanup(self): retval = True errmsg = '' try: vdns = self.vnc_lib.virtual_DNS_read(fq_name=self.vdns_fq_name) errmsg = errmsg + "VDNS info " + \ self.vdns_fq_name + 'still not removed' self.logger.warn(errmsg) return False, errmsg except NoIdError: self.logger.info("VDNS info: %s deleted successfully." % self.vdns_fq_name) status = self.verify_vdns_not_in_api_server() if not status: retval = retval and False errmsg = errmsg + "\nVdns info is not deleted from API Server" status = self.verify_vdns_not_in_control_node() if not status: retval = retval and False errmsg = errmsg + "\n VDNS info is not deleted from control node" if not retval: return False, errmsg return True, errmsg class VdnsRecordFixture(ContrailFixture): def __init__(self, inputs, connections, virtual_DNS_record_name, parent_fixt, virtual_DNS_record_data): self.logger = inputs.logger self.vnc_lib = connections.vnc_lib self.api_s_inspect = connections.api_server_inspect self.cn_inspect = connections.cn_inspect self.inputs = inputs self.vdns_record_name = virtual_DNS_record_name self.parent = parent_fixt self.vdns_record_data = virtual_DNS_record_data self.obj = None def setUp(self): self.logger.debug("Creating VDNS record data : %s", self.vdns_record_name) super(VdnsRecordFixture, self).setUp() self.vdns_rec_fix = self.useFixture(VirtualDnsRecordTestFixtureGen( self.vnc_lib, virtual_DNS_record_name=self.vdns_record_name, parent_fixt=self.parent, virtual_DNS_record_data=self.vdns_record_data, auto_prop_val=True)) self.obj = self.vdns_rec_fix.getObj() self.vdns_rec_fq_name = self.obj.get_fq_name_str() def cleanUp(self): self.logger.debug("Deleting VDNS record data: %s", self.vdns_record_name) super(VdnsRecordFixture, self).cleanUp() result, msg = self.verify_on_cleanup() assert result, msg def verify_on_setup(self): retval = True errmsg = '' self.logger.info("In verify_on_setup") try: vdns_rec = self.vnc_lib.virtual_DNS_record_read( fq_name=self.obj.get_fq_name()) self.logger.debug( "VDNS record: %s created succesfully", self.obj.get_fq_name()) except NoIdError: errmsg = errmsg + \ "\n VDNS record: %s not created." % self.obj.get_fq_name() self.logger.warn(errmsg) return False, errmsg self.logger.info("Verify VDNS record is shown in the API server") ret_val1 = self.verify_vdns_rec_in_api_server() if not ret_val1: retval = True and False errmsg = errmsg + "\n VDNS record " + \ self.obj.get_fq_name() + \ " is info not found in the control node\n" self.logger.error( "VDNS record info not found not found in control node") self.logger.info("Verify VDNS record is shown in the control node") ret_val2 = self.verify_vdns_rec_in_cn_node() if not ret_val2: retval = True and False errmsg = errmsg + "\n VDNS record " + \ self.obj.get_fq_name() + \ " is info not found in the control node\n" self.logger.error( "VDNS record info not found not found in the control node") self.logger.info("Out of verify_on_setup") return retval, errmsg # end of verify_on_setup def verify_on_cleanup(self): retval = True errmsg = '' try: vdns = self.vnc_lib.virtual_DNS_record_read( fq_name=self.vdns_rec_fq_name) errmsg = errmsg + 'VDNS record ' + \ self.vdns_rec_fq_name + ' info still not removed' self.logger.warn(errmsg) return False, errmsg except NoIdError: self.logger.info( "VDNS record info: %s deleted successfully.", self.vdns_rec_fq_name) return retval, errmsg status = self.verify_vdns_rec_not_in_api_server() if not status: retval = retval and False errmsg = errmsg + \ "\nVDNS record info is not deleted from API server" status = self.verify_vdns_rec_not_in_control_node() if not status: retval = retval and False errmsg = errmsg + \ "\nVDNS record info is not deleted from control node" if not retval: return False, errmsg return True, errmsg # end of verify_on_cleanup @retry(delay=5, tries=5) def verify_vdns_rec_in_cn_node(self): ''' verify VDNS record data in API in Control node''' self.logger.info('Inside verify_vdns_rec_in_cn_node') result = True msg = '' for cn in self.inputs.bgp_ips: try: cn_s_dns = self.cn_inspect[cn].get_cn_vdns_rec( vdns=str(self.parent.getObj().name), rec_name=str(self.obj.name)) if self.obj.get_fq_name_str() not in cn_s_dns['node_name']: result = result and False msg = msg + \ '\nvdns name info not matching with control name data' act_cn_vdns_rec_data = cn_s_dns['obj_info'][ 'data']['virtual-DNS-record-data'] exp_vdns_rec_data = self.obj.get_virtual_DNS_record_data() if act_cn_vdns_rec_data: if exp_vdns_rec_data.__dict__['record_name'] != act_cn_vdns_rec_data['record-name']: result = result and False msg = msg + \ '\nvdns record name is not matching with control node data' if str(exp_vdns_rec_data.__dict__['record_ttl_seconds']) != act_cn_vdns_rec_data['record-ttl-seconds']: result = result and False msg = msg + \ '\nvdns record ttl value is not matching with control node data' if exp_vdns_rec_data.__dict__['record_type'] != act_cn_vdns_rec_data['record-type']: result = result and False msg = msg + \ '\nvdns record type value is not matching with control node data' if exp_vdns_rec_data.__dict__['record_data'] != act_cn_vdns_rec_data['record-data']: result = result and False msg = msg + \ '\nvdns record data is not matching with control node data' except Exception as e: # Return false if we get an key error and for retry return False self.logger.info("Outside verify_vdns_rec_in_cn_node") if msg != '': self.logger.info( "VDNS record info is not matching with control node data\n %s:", msg) return result self.logger.info('Outside verify_vdns_rec_in_cn_node') # end of verify_vdns_rec_in_cn_node @retry(delay=5, tries=5) def verify_vdns_rec_in_api_server(self): ''' verify VDNS record data in API server ''' self.logger.info("Inside verify_vdns_rec_in_api_server") result = True api_s_dns_rec = self.api_s_inspect.get_cs_dns_rec( rec_name=self.vdns_record_name, vdns_name=self.parent.getObj().name, refresh=True) msg = '' try: if self.obj.get_fq_name() != api_s_dns_rec['virtual-DNS-record']['fq_name']: result = result and False msg = msg + \ '\n fq name data is not matching with DNS record data' if self.obj.uuid != api_s_dns_rec['virtual-DNS-record']['uuid']: result = result and False msg = msg + '\n UUID is is not matching with DNS record data' api_vdns_rec_data = api_s_dns_rec[ 'virtual-DNS-record']['virtual_DNS_record_data'] exp_vdns_rec_data = self.obj.get_virtual_DNS_record_data() for data in api_vdns_rec_data: if str(exp_vdns_rec_data.__dict__[data]) != str(api_vdns_rec_data.get(data)): result = result and False msg = msg + '\nvdns ' + data + \ ' is not matching with api server DNS record data' except Exception as e: # Return false if we get an key error and for retry return False if msg != '': self.logger.info( "VDNS record info is not matching with API Server data\n %s:", msg) self.logger.info("Outside verify_vdns_rec_in_api_server") return result # end of verify_vdns_rec_in_api_server @retry(delay=2, tries=5) def verify_vdns_rec_not_in_api_server(self): '''Validate VDNS record data not in API-Server.''' if self.api_s_inspect.get_cs_dns_rec(rec_name=self.vdns_record_name, vdns_name=self.parent.getObj().name, refresh=True) is not None: errmsg = "VDNS record information %s still found in the API Server" % self.obj.name self.logger.warn(errmsg) return False else: self.logger.info( "VDNS record information %s removed from the API Server", self.obj.name) return True @retry(delay=2, tries=5) def verify_vdns_rec_not_in_control_node(self): for cn in self.inputs.bgp_ips: cn_s_dns = self.cn_inspect[cn].get_cn_vdns_rec( vdns=str(self.parent.getObj().name), rec_name=str(self.obj.name)) if cn_s_dns: errmsg = "VDNS record information %s still found in the Control node" % self.obj.name self.logger.warn(errmsg) return False else: self.logger.info( "VDNS record information %s removed in the Control node", self.obj.name) return True

44.955665

165

0.580868

2,364

18,252

4.233926

0.057107

0.046958

0.037766

0.030572

0.898491

0.851134

0.790688

0.745329

0.701669

0.653911

0

0.001981

0.336237

18,252

405

166

45.066667

0.824185

0.02082

0

0.56546

0

0.198704

0.01626

0

0.005571

0

null

0

0.016713

null

0.005571

0

null

0

1

0

null

0

1

0

7

27948ac90ecf3a35a9c1e2e1a6924b059f76fc90

308

py

Python

cross_circle_gym/envs/__init__.py

ivegner/PyDSRL

26d8d380883fef04b21a62a2cf7b0202f84dcc32

[ "MIT" ]

14

2018-02-28T19:50:07.000Z

2021-05-05T03:09:26.000Z

cross_circle_gym/envs/__init__.py

calyri/PyDSRL

b531603cb56fc55dac5a621287b76bcba0ed015d

[ "MIT" ]

5

2019-09-25T15:42:31.000Z

2021-03-23T11:30:16.000Z

cross_circle_gym/envs/__init__.py

calyri/PyDSRL

b531603cb56fc55dac5a621287b76bcba0ed015d

[ "MIT" ]

6

2018-04-19T13:04:06.000Z

2021-05-18T04:30:57.000Z

from cross_circle_gym.envs.cross_circle_neg_grid import CrossCircleNegGrid from cross_circle_gym.envs.cross_circle_mixed_grid import CrossCircleMixedGrid from cross_circle_gym.envs.cross_circle_neg_rand import CrossCircleNegRand from cross_circle_gym.envs.cross_circle_mixed_rand import CrossCircleMixedRand

61.6

78

0.922078

44

308

6

0.318182

0.333333

0.227273

0.272727

0.560606

0

0.051948

308

4

79

77

0.90411

0

1

0

true

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

27a80f25642d7fdb465294b17fbb998b82a85e22

18,008

py

Python

tests/test_base.py

onkelbeh/gios

1ede07890dc8fd6c22d641999b0d2df7f883fccf

[ "Apache-2.0" ]

null

tests/test_base.py

onkelbeh/gios

1ede07890dc8fd6c22d641999b0d2df7f883fccf

[ "Apache-2.0" ]

null

tests/test_base.py

onkelbeh/gios

1ede07890dc8fd6c22d641999b0d2df7f883fccf

[ "Apache-2.0" ]

null

"""Tests for gios package.""" import json import aiohttp import pytest from aioresponses import aioresponses from gios import ApiError, Gios, InvalidSensorsData, NoStationError INVALID_STATION_ID = 0 VALID_STATION_ID = 552 VALID_STATION_NAME = "Test Name" VALID_LATITUDE = "99.99" VALID_LONGITUDE = "88.88" @pytest.mark.asyncio async def test_valid_data_first_value(): # pylint:disable=too-many-statements """Test with valid data and valid first sensor's value.""" with open("tests/data/stations.json") as file: stations = json.load(file) with open("tests/data/station.json") as file: station = json.load(file) with open("tests/data/sensor_658.json") as file: sensor_658 = json.load(file) with open("tests/data/sensor_660.json") as file: sensor_660 = json.load(file) with open("tests/data/sensor_665.json") as file: sensor_665 = json.load(file) with open("tests/data/sensor_667.json") as file: sensor_667 = json.load(file) with open("tests/data/sensor_670.json") as file: sensor_670 = json.load(file) with open("tests/data/sensor_672.json") as file: sensor_672 = json.load(file) with open("tests/data/sensor_14395.json") as file: sensor_14395 = json.load(file) with open("tests/data/indexes.json") as file: indexes = json.load(file) session = aiohttp.ClientSession() with aioresponses() as session_mock: session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/station/findAll", payload=stations, ) session_mock.get( f"http://api.gios.gov.pl/pjp-api/rest/station/sensors/{VALID_STATION_ID}", payload=station, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/672", payload=sensor_672, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/658", payload=sensor_658, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/660", payload=sensor_660, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/665", payload=sensor_665, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/667", payload=sensor_667, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/670", payload=sensor_670, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/14395", payload=sensor_14395, ) session_mock.get( f"http://api.gios.gov.pl/pjp-api/rest/aqindex/getIndex/{VALID_STATION_ID}", payload=indexes, ) gios = Gios(VALID_STATION_ID, session) await gios.update() await session.close() assert gios.station_name == VALID_STATION_NAME assert gios.station_id == VALID_STATION_ID assert gios.latitude == VALID_LATITUDE assert gios.longitude == VALID_LONGITUDE assert len(gios.data) == 8 assert gios.data["SO2"]["value"] == 11.6502 assert gios.data["SO2"]["index"] == "very good" assert gios.data["C6H6"]["value"] == 2.57148 assert gios.data["C6H6"]["index"] == "very good" assert gios.data["CO"]["value"] == 786.702 assert gios.data["CO"]["index"] == "very good" assert gios.data["NO2"]["value"] == 59.9545 assert gios.data["NO2"]["index"] == "very good" assert gios.data["O3"]["value"] == 8.63111 assert gios.data["O3"]["index"] == "good" assert gios.data["PM2.5"]["value"] == 59.9428 assert gios.data["PM2.5"]["index"] == "very good" assert gios.data["PM10"]["value"] == 123.879 assert gios.data["PM10"]["index"] == "very good" assert gios.data["AQI"]["value"] == "good" @pytest.mark.asyncio async def test_api_error(): """Test GIOS API error.""" session = aiohttp.ClientSession() with aioresponses() as session_mock: session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/station/findAll", status=404, ) gios = Gios(VALID_STATION_ID, session) try: await gios.update() except ApiError as error: assert str(error.status) == "404" await session.close() @pytest.mark.asyncio async def test_valid_data_second_value(): # pylint:disable=too-many-statements """Test with valid data and valid second sensor's value.""" with open("tests/data/stations.json") as file: stations = json.load(file) with open("tests/data/station.json") as file: station = json.load(file) with open("tests/data/sensor_658.json") as file: sensor_658 = json.load(file) with open("tests/data/sensor_660.json") as file: sensor_660 = json.load(file) with open("tests/data/sensor_665.json") as file: sensor_665 = json.load(file) with open("tests/data/sensor_667.json") as file: sensor_667 = json.load(file) with open("tests/data/sensor_670.json") as file: sensor_670 = json.load(file) with open("tests/data/sensor_672.json") as file: sensor_672 = json.load(file) with open("tests/data/sensor_14395.json") as file: sensor_14395 = json.load(file) with open("tests/data/indexes.json") as file: indexes = json.load(file) sensor_658["values"][0]["value"] = None sensor_660["values"][0]["value"] = None sensor_665["values"][0]["value"] = None sensor_667["values"][0]["value"] = None sensor_670["values"][0]["value"] = None sensor_672["values"][0]["value"] = None sensor_14395["values"][0]["value"] = None session = aiohttp.ClientSession() with aioresponses() as session_mock: session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/station/findAll", payload=stations, ) session_mock.get( f"http://api.gios.gov.pl/pjp-api/rest/station/sensors/{VALID_STATION_ID}", payload=station, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/672", payload=sensor_672, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/658", payload=sensor_658, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/660", payload=sensor_660, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/665", payload=sensor_665, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/667", payload=sensor_667, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/670", payload=sensor_670, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/14395", payload=sensor_14395, ) session_mock.get( f"http://api.gios.gov.pl/pjp-api/rest/aqindex/getIndex/{VALID_STATION_ID}", payload=indexes, ) gios = Gios(VALID_STATION_ID, session) await gios.update() await session.close() assert gios.station_name == VALID_STATION_NAME assert gios.station_id == VALID_STATION_ID assert gios.latitude == VALID_LATITUDE assert gios.longitude == VALID_LONGITUDE assert len(gios.data) == 8 assert gios.data["SO2"]["value"] == 11.501 assert gios.data["SO2"]["index"] == "very good" assert gios.data["C6H6"]["value"] == 3.24432 assert gios.data["C6H6"]["index"] == "very good" assert gios.data["CO"]["value"] == 1041.74 assert gios.data["CO"]["index"] == "very good" assert gios.data["NO2"]["value"] == 52.6198 assert gios.data["NO2"]["index"] == "very good" assert gios.data["O3"]["value"] == 4.93778 assert gios.data["O3"]["index"] == "good" assert gios.data["PM2.5"]["value"] == 72.0243 assert gios.data["PM2.5"]["index"] == "very good" assert gios.data["PM10"]["value"] == 115.559 assert gios.data["PM10"]["index"] == "very good" assert gios.data["AQI"]["value"] == "good" @pytest.mark.asyncio async def test_no_indexes_data(): """Test with valid data.""" with open("tests/data/stations.json") as file: stations = json.load(file) with open("tests/data/station.json") as file: station = json.load(file) with open("tests/data/sensor_658.json") as file: sensor_658 = json.load(file) with open("tests/data/sensor_660.json") as file: sensor_660 = json.load(file) with open("tests/data/sensor_665.json") as file: sensor_665 = json.load(file) with open("tests/data/sensor_667.json") as file: sensor_667 = json.load(file) with open("tests/data/sensor_670.json") as file: sensor_670 = json.load(file) with open("tests/data/sensor_672.json") as file: sensor_672 = json.load(file) with open("tests/data/sensor_14395.json") as file: sensor_14395 = json.load(file) session = aiohttp.ClientSession() with aioresponses() as session_mock: session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/station/findAll", payload=stations, ) session_mock.get( f"http://api.gios.gov.pl/pjp-api/rest/station/sensors/{VALID_STATION_ID}", payload=station, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/672", payload=sensor_672, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/658", payload=sensor_658, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/660", payload=sensor_660, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/665", payload=sensor_665, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/667", payload=sensor_667, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/670", payload=sensor_670, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/14395", payload=sensor_14395, ) session_mock.get( f"http://api.gios.gov.pl/pjp-api/rest/aqindex/getIndex/{VALID_STATION_ID}", payload={}, ) gios = Gios(VALID_STATION_ID, session) try: await gios.update() except InvalidSensorsData as error: assert str(error.status) == "Invalid index data from GIOS API" await session.close() @pytest.mark.asyncio async def test_no_sensor_data_1(): # pylint:disable=too-many-statements """Test with no sensor data.""" with open("tests/data/stations.json") as file: stations = json.load(file) with open("tests/data/station.json") as file: station = json.load(file) with open("tests/data/sensor_658.json") as file: sensor_658 = json.load(file) with open("tests/data/sensor_660.json") as file: sensor_660 = json.load(file) with open("tests/data/sensor_665.json") as file: sensor_665 = json.load(file) with open("tests/data/sensor_667.json") as file: sensor_667 = json.load(file) with open("tests/data/sensor_670.json") as file: sensor_670 = json.load(file) with open("tests/data/sensor_672.json") as file: sensor_672 = json.load(file) with open("tests/data/sensor_14395.json") as file: sensor_14395 = json.load(file) with open("tests/data/indexes.json") as file: indexes = json.load(file) sensor_658["values"][0]["value"] = None sensor_658["values"][1]["value"] = None sensor_660["values"][0]["value"] = None sensor_660["values"][1]["value"] = None sensor_665["values"][0]["value"] = None sensor_665["values"][1]["value"] = None sensor_667["values"][0]["value"] = None sensor_667["values"][1]["value"] = None sensor_670["values"][0]["value"] = None sensor_670["values"][1]["value"] = None sensor_672["values"][0]["value"] = None sensor_672["values"][1]["value"] = None sensor_14395["values"][0]["value"] = None sensor_14395["values"][1]["value"] = None session = aiohttp.ClientSession() with aioresponses() as session_mock: session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/station/findAll", payload=stations, ) session_mock.get( f"http://api.gios.gov.pl/pjp-api/rest/station/sensors/{VALID_STATION_ID}", payload=station, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/672", payload=sensor_672, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/658", payload=sensor_658, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/660", payload=sensor_660, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/665", payload=sensor_665, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/667", payload=sensor_667, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/670", payload=sensor_670, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/14395", payload=sensor_14395, ) session_mock.get( f"http://api.gios.gov.pl/pjp-api/rest/aqindex/getIndex/{VALID_STATION_ID}", payload=indexes, ) gios = Gios(VALID_STATION_ID, session) try: await gios.update() except InvalidSensorsData as error: assert str(error.status) == "Invalid sensor data from GIOS API" await session.close() @pytest.mark.asyncio async def test_invalid_sensor_data_2(): """Test with invalid sensor data.""" with open("tests/data/stations.json") as file: stations = json.load(file) with open("tests/data/station.json") as file: station = json.load(file) session = aiohttp.ClientSession() with aioresponses() as session_mock: session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/station/findAll", payload=stations, ) session_mock.get( f"http://api.gios.gov.pl/pjp-api/rest/station/sensors/{VALID_STATION_ID}", payload=station, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/672", payload=None, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/658", payload=None, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/660", payload=None, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/665", payload=None, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/667", payload=None, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/670", payload=None, ) session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/data/getData/14395", payload=None, ) gios = Gios(VALID_STATION_ID, session) try: await gios.update() except InvalidSensorsData as error: assert str(error.status) == "Invalid sensor data from GIOS API" await session.close() @pytest.mark.asyncio async def test_no_station_data(): """Test with no station data.""" with open("tests/data/stations.json") as file: stations = json.load(file) session = aiohttp.ClientSession() with aioresponses() as session_mock: session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/station/findAll", payload=stations, ) session_mock.get( f"http://api.gios.gov.pl/pjp-api/rest/station/sensors/{VALID_STATION_ID}", payload={}, ) gios = Gios(VALID_STATION_ID, session) try: await gios.update() except InvalidSensorsData as error: assert str(error.status) == "Invalid measuring station data from GIOS API" await session.close() @pytest.mark.asyncio async def test_no_stations_data(): """Test with no stations data.""" session = aiohttp.ClientSession() with aioresponses() as session_mock: session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/station/findAll", payload={}, ) gios = Gios(VALID_STATION_ID, session) try: await gios.update() except ApiError as error: assert str(error.status) == "Invalid measuring stations list from GIOS API" await session.close() @pytest.mark.asyncio async def test_invalid_station_id(): """Test with invalid station_id.""" with open("tests/data/stations.json") as file: stations = json.load(file) session = aiohttp.ClientSession() with aioresponses() as session_mock: session_mock.get( "http://api.gios.gov.pl/pjp-api/rest/station/findAll", payload=stations, ) gios = Gios(INVALID_STATION_ID, session) try: await gios.update() except NoStationError as error: assert str(error.status) == "0 is not a valid measuring station ID" await session.close()

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1

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null

0

7

27b186a35b3626619ffb5d91bec020f8bfc12850

15,260

py

Python

swagger_client/api/search_api.py

rseichter/bootini-star

a80258f01a05e4df38748b8cb47dfadabd42c20d

[ "MIT" ]

null

swagger_client/api/search_api.py

rseichter/bootini-star

a80258f01a05e4df38748b8cb47dfadabd42c20d

[ "MIT" ]

null

swagger_client/api/search_api.py

rseichter/bootini-star

a80258f01a05e4df38748b8cb47dfadabd42c20d

[ "MIT" ]

null

# coding: utf-8 """ EVE Swagger Interface An OpenAPI for EVE Online # noqa: E501 OpenAPI spec version: 0.8.0 Generated by: https://github.com/swagger-api/swagger-codegen.git """ from __future__ import absolute_import import re # noqa: F401 # python 2 and python 3 compatibility library import six from swagger_client.api_client import ApiClient class SearchApi(object): """NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. Ref: https://github.com/swagger-api/swagger-codegen """ def __init__(self, api_client=None): if api_client is None: api_client = ApiClient() self.api_client = api_client def get_characters_character_id_search(self, categories, character_id, search, **kwargs): # noqa: E501 """Search on a string # noqa: E501 Search for entities that match a given sub-string. --- This route is cached for up to 3600 seconds # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.get_characters_character_id_search(categories, character_id, search, async=True) >>> result = thread.get() :param async bool :param list[str] categories: Type of entities to search for (required) :param int character_id: An EVE character ID (required) :param str search: The string to search on (required) :param str datasource: The server name you would like data from :param str language: Language to use in the response :param bool strict: Whether the search should be a strict match :param str token: Access token to use if unable to set a header :param str user_agent: Client identifier, takes precedence over headers :param str x_user_agent: Client identifier, takes precedence over User-Agent :return: GetCharactersCharacterIdSearchOk If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.get_characters_character_id_search_with_http_info(categories, character_id, search, **kwargs) # noqa: E501 else: (data) = self.get_characters_character_id_search_with_http_info(categories, character_id, search, **kwargs) # noqa: E501 return data def get_characters_character_id_search_with_http_info(self, categories, character_id, search, **kwargs): # noqa: E501 """Search on a string # noqa: E501 Search for entities that match a given sub-string. --- This route is cached for up to 3600 seconds # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.get_characters_character_id_search_with_http_info(categories, character_id, search, async=True) >>> result = thread.get() :param async bool :param list[str] categories: Type of entities to search for (required) :param int character_id: An EVE character ID (required) :param str search: The string to search on (required) :param str datasource: The server name you would like data from :param str language: Language to use in the response :param bool strict: Whether the search should be a strict match :param str token: Access token to use if unable to set a header :param str user_agent: Client identifier, takes precedence over headers :param str x_user_agent: Client identifier, takes precedence over User-Agent :return: GetCharactersCharacterIdSearchOk If the method is called asynchronously, returns the request thread. """ all_params = ['categories', 'character_id', 'search', 'datasource', 'language', 'strict', 'token', 'user_agent', 'x_user_agent'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method get_characters_character_id_search" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'categories' is set if ('categories' not in params or params['categories'] is None): raise ValueError("Missing the required parameter `categories` when calling `get_characters_character_id_search`") # noqa: E501 # verify the required parameter 'character_id' is set if ('character_id' not in params or params['character_id'] is None): raise ValueError("Missing the required parameter `character_id` when calling `get_characters_character_id_search`") # noqa: E501 # verify the required parameter 'search' is set if ('search' not in params or params['search'] is None): raise ValueError("Missing the required parameter `search` when calling `get_characters_character_id_search`") # noqa: E501 if ('categories' in params and len(params['categories']) > 11): raise ValueError("Invalid value for parameter `categories` when calling `get_characters_character_id_search`, number of items must be less than or equal to `11`") # noqa: E501 if ('categories' in params and len(params['categories']) < 1): raise ValueError("Invalid value for parameter `categories` when calling `get_characters_character_id_search`, number of items must be greater than or equal to `1`") # noqa: E501 if 'character_id' in params and params['character_id'] < 1: # noqa: E501 raise ValueError("Invalid value for parameter `character_id` when calling `get_characters_character_id_search`, must be a value greater than or equal to `1`") # noqa: E501 if ('search' in params and len(params['search']) < 3): raise ValueError("Invalid value for parameter `search` when calling `get_characters_character_id_search`, length must be greater than or equal to `3`") # noqa: E501 collection_formats = {} path_params = {} if 'character_id' in params: path_params['character_id'] = params['character_id'] # noqa: E501 query_params = [] if 'categories' in params: query_params.append(('categories', params['categories'])) # noqa: E501 collection_formats['categories'] = 'csv' # noqa: E501 if 'datasource' in params: query_params.append(('datasource', params['datasource'])) # noqa: E501 if 'language' in params: query_params.append(('language', params['language'])) # noqa: E501 if 'search' in params: query_params.append(('search', params['search'])) # noqa: E501 if 'strict' in params: query_params.append(('strict', params['strict'])) # noqa: E501 if 'token' in params: query_params.append(('token', params['token'])) # noqa: E501 if 'user_agent' in params: query_params.append(('user_agent', params['user_agent'])) # noqa: E501 header_params = {} if 'x_user_agent' in params: header_params['X-User-Agent'] = params['x_user_agent'] # noqa: E501 form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['evesso'] # noqa: E501 return self.api_client.call_api( '/v3/characters/{character_id}/search/', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='GetCharactersCharacterIdSearchOk', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def get_search(self, categories, search, **kwargs): # noqa: E501 """Search on a string # noqa: E501 Search for entities that match a given sub-string. --- This route is cached for up to 3600 seconds # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.get_search(categories, search, async=True) >>> result = thread.get() :param async bool :param list[str] categories: Type of entities to search for (required) :param str search: The string to search on (required) :param str datasource: The server name you would like data from :param str language: Language to use in the response :param bool strict: Whether the search should be a strict match :param str user_agent: Client identifier, takes precedence over headers :param str x_user_agent: Client identifier, takes precedence over User-Agent :return: GetSearchOk If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.get_search_with_http_info(categories, search, **kwargs) # noqa: E501 else: (data) = self.get_search_with_http_info(categories, search, **kwargs) # noqa: E501 return data def get_search_with_http_info(self, categories, search, **kwargs): # noqa: E501 """Search on a string # noqa: E501 Search for entities that match a given sub-string. --- This route is cached for up to 3600 seconds # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.get_search_with_http_info(categories, search, async=True) >>> result = thread.get() :param async bool :param list[str] categories: Type of entities to search for (required) :param str search: The string to search on (required) :param str datasource: The server name you would like data from :param str language: Language to use in the response :param bool strict: Whether the search should be a strict match :param str user_agent: Client identifier, takes precedence over headers :param str x_user_agent: Client identifier, takes precedence over User-Agent :return: GetSearchOk If the method is called asynchronously, returns the request thread. """ all_params = ['categories', 'search', 'datasource', 'language', 'strict', 'user_agent', 'x_user_agent'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method get_search" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'categories' is set if ('categories' not in params or params['categories'] is None): raise ValueError("Missing the required parameter `categories` when calling `get_search`") # noqa: E501 # verify the required parameter 'search' is set if ('search' not in params or params['search'] is None): raise ValueError("Missing the required parameter `search` when calling `get_search`") # noqa: E501 if ('categories' in params and len(params['categories']) > 10): raise ValueError("Invalid value for parameter `categories` when calling `get_search`, number of items must be less than or equal to `10`") # noqa: E501 if ('categories' in params and len(params['categories']) < 1): raise ValueError("Invalid value for parameter `categories` when calling `get_search`, number of items must be greater than or equal to `1`") # noqa: E501 if ('search' in params and len(params['search']) < 3): raise ValueError("Invalid value for parameter `search` when calling `get_search`, length must be greater than or equal to `3`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] if 'categories' in params: query_params.append(('categories', params['categories'])) # noqa: E501 collection_formats['categories'] = 'csv' # noqa: E501 if 'datasource' in params: query_params.append(('datasource', params['datasource'])) # noqa: E501 if 'language' in params: query_params.append(('language', params['language'])) # noqa: E501 if 'search' in params: query_params.append(('search', params['search'])) # noqa: E501 if 'strict' in params: query_params.append(('strict', params['strict'])) # noqa: E501 if 'user_agent' in params: query_params.append(('user_agent', params['user_agent'])) # noqa: E501 header_params = {} if 'x_user_agent' in params: header_params['X-User-Agent'] = params['x_user_agent'] # noqa: E501 form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = [] # noqa: E501 return self.api_client.call_api( '/v2/search/', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='GetSearchOk', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats)

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0.039758

0.043053

0.923249

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0.892952

0.872329

0.867864

0

0.019219

0.273722

15,260

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191

48.598726

0.829559

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0

null

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null

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null

0

1

0

1

0

null

0

1

0

9

fdd60091a972656ef68fa473ed8bb547223de8c7

1,547

py

Python

plugin/vimtools/tests/test_insert.py

dsw7/VimTools

2204f3a64d1cf6d1aa1811d4b7e2ae47832e9097

[ "MIT" ]

null

plugin/vimtools/tests/test_insert.py

dsw7/VimTools

2204f3a64d1cf6d1aa1811d4b7e2ae47832e9097

[ "MIT" ]

6

2020-06-14T06:18:20.000Z

2021-05-25T03:40:08.000Z

plugin/vimtools/tests/test_insert.py

dsw7/VimTools

2204f3a64d1cf6d1aa1811d4b7e2ae47832e9097

[ "MIT" ]

null

from helpers import VimToolsTestCase class TestIns(VimToolsTestCase): def setUp(self): self.input_string = """\ foo bar baz foo bar baz foo bar baz foo bar baz foo bar baz foo bar baz foo bar baz foo bar baz foo bar baz foo bar baz """ def test_comment_out_python(self): expected_string = """\ #foo bar baz #foo bar baz foo bar baz foo bar baz foo bar baz foo bar baz foo bar baz foo bar baz foo bar baz foo bar baz """ command = [":Ins # 1 2"] self.assert_files_equal(command, self.input_string, expected_string) def test_comment_out_python_two_digit_range(self): expected_string = """\ foo bar baz foo bar baz foo bar baz foo bar baz foo bar baz #foo bar baz #foo bar baz #foo bar baz #foo bar baz #foo bar baz """ command = [":Ins # 6 10"] self.assert_files_equal(command, self.input_string, expected_string) def test_comment_out_cpp(self): expected_string = """\ foo bar baz //foo bar baz //foo bar baz foo bar baz foo bar baz foo bar baz foo bar baz foo bar baz foo bar baz foo bar baz """ command = [r":Ins \/\/ 2 3"] self.assert_files_equal(command, self.input_string, expected_string)

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e32e4ea87b22279be9927d76d8008e7e312ea318

36,528

py

Python

sdk/python/pulumi_wavefront/cloud_integration_cloud_watch.py

pulumi/pulumi-wavefront

1d199d386ee241fa2ef94553e6cae1359ec9ccf6

[ "ECL-2.0", "Apache-2.0" ]

1

2022-02-20T09:48:33.000Z

sdk/python/pulumi_wavefront/cloud_integration_cloud_watch.py

pulumi/pulumi-wavefront

1d199d386ee241fa2ef94553e6cae1359ec9ccf6

[ "ECL-2.0", "Apache-2.0" ]

40

2020-08-12T08:37:24.000Z

2022-03-31T15:51:17.000Z

sdk/python/pulumi_wavefront/cloud_integration_cloud_watch.py

pulumi/pulumi-wavefront

1d199d386ee241fa2ef94553e6cae1359ec9ccf6

[ "ECL-2.0", "Apache-2.0" ]

null

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. *** # *** 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, overload from . import _utilities __all__ = ['CloudIntegrationCloudWatchArgs', 'CloudIntegrationCloudWatch'] @pulumi.input_type class CloudIntegrationCloudWatchArgs: def __init__(__self__, *, external_id: pulumi.Input[str], role_arn: pulumi.Input[str], service: pulumi.Input[str], additional_tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, force_save: Optional[pulumi.Input[bool]] = None, instance_selection_tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, metric_filter_regex: Optional[pulumi.Input[str]] = None, name: Optional[pulumi.Input[str]] = None, namespaces: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, point_tag_filter_regex: Optional[pulumi.Input[str]] = None, service_refresh_rate_in_minutes: Optional[pulumi.Input[int]] = None, volume_selection_tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None): """ The set of arguments for constructing a CloudIntegrationCloudWatch resource. :param pulumi.Input[str] external_id: The Role ARN that the customer has created in AWS IAM to allow access to Wavefront :param pulumi.Input[str] role_arn: The external id corresponding to the Role ARN :param pulumi.Input[str] service: A value denoting which cloud service this service integrates with :param pulumi.Input[Mapping[str, pulumi.Input[str]]] additional_tags: A list of point tag key-values to add to every point ingested using this integration :param pulumi.Input[bool] force_save: Forces this resource to save, even if errors are present :param pulumi.Input[Mapping[str, pulumi.Input[str]]] instance_selection_tags: A string->string map whitelist of instance tag-value pairs (in AWS). If the instance's AWS tags match this whitelist, CloudWatch data about this instance is ingested. Multiple entries are OR'ed :param pulumi.Input[str] metric_filter_regex: A regular expression that a CloudWatch metric name must match (case-insensitively) in order to be ingested :param pulumi.Input[str] name: The human-readable name of this integration :param pulumi.Input[Sequence[pulumi.Input[str]]] namespaces: A list of namespaces that limit what we query from CloudWatch :param pulumi.Input[str] point_tag_filter_regex: A regular expression that AWS tag key name must match (case-insensitively) in order to be ingested :param pulumi.Input[int] service_refresh_rate_in_minutes: How often, in minutes, to refresh the service :param pulumi.Input[Mapping[str, pulumi.Input[str]]] volume_selection_tags: A string->string map of whitelist of volume tag-value pairs (in AWS). If the volume's AWS tags match this whitelist, CloudWatch data about this volume is ingested. Multiple entries are OR'ed """ pulumi.set(__self__, "external_id", external_id) pulumi.set(__self__, "role_arn", role_arn) pulumi.set(__self__, "service", service) if additional_tags is not None: pulumi.set(__self__, "additional_tags", additional_tags) if force_save is not None: pulumi.set(__self__, "force_save", force_save) if instance_selection_tags is not None: pulumi.set(__self__, "instance_selection_tags", instance_selection_tags) if metric_filter_regex is not None: pulumi.set(__self__, "metric_filter_regex", metric_filter_regex) if name is not None: pulumi.set(__self__, "name", name) if namespaces is not None: pulumi.set(__self__, "namespaces", namespaces) if point_tag_filter_regex is not None: pulumi.set(__self__, "point_tag_filter_regex", point_tag_filter_regex) if service_refresh_rate_in_minutes is not None: pulumi.set(__self__, "service_refresh_rate_in_minutes", service_refresh_rate_in_minutes) if volume_selection_tags is not None: pulumi.set(__self__, "volume_selection_tags", volume_selection_tags) @property @pulumi.getter(name="externalId") def external_id(self) -> pulumi.Input[str]: """ The Role ARN that the customer has created in AWS IAM to allow access to Wavefront """ return pulumi.get(self, "external_id") @external_id.setter def external_id(self, value: pulumi.Input[str]): pulumi.set(self, "external_id", value) @property @pulumi.getter(name="roleArn") def role_arn(self) -> pulumi.Input[str]: """ The external id corresponding to the Role ARN """ return pulumi.get(self, "role_arn") @role_arn.setter def role_arn(self, value: pulumi.Input[str]): pulumi.set(self, "role_arn", value) @property @pulumi.getter def service(self) -> pulumi.Input[str]: """ A value denoting which cloud service this service integrates with """ return pulumi.get(self, "service") @service.setter def service(self, value: pulumi.Input[str]): pulumi.set(self, "service", value) @property @pulumi.getter(name="additionalTags") def additional_tags(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]: """ A list of point tag key-values to add to every point ingested using this integration """ return pulumi.get(self, "additional_tags") @additional_tags.setter def additional_tags(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]): pulumi.set(self, "additional_tags", value) @property @pulumi.getter(name="forceSave") def force_save(self) -> Optional[pulumi.Input[bool]]: """ Forces this resource to save, even if errors are present """ return pulumi.get(self, "force_save") @force_save.setter def force_save(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "force_save", value) @property @pulumi.getter(name="instanceSelectionTags") def instance_selection_tags(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]: """ A string->string map whitelist of instance tag-value pairs (in AWS). If the instance's AWS tags match this whitelist, CloudWatch data about this instance is ingested. Multiple entries are OR'ed """ return pulumi.get(self, "instance_selection_tags") @instance_selection_tags.setter def instance_selection_tags(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]): pulumi.set(self, "instance_selection_tags", value) @property @pulumi.getter(name="metricFilterRegex") def metric_filter_regex(self) -> Optional[pulumi.Input[str]]: """ A regular expression that a CloudWatch metric name must match (case-insensitively) in order to be ingested """ return pulumi.get(self, "metric_filter_regex") @metric_filter_regex.setter def metric_filter_regex(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "metric_filter_regex", value) @property @pulumi.getter def name(self) -> Optional[pulumi.Input[str]]: """ The human-readable name of this integration """ return pulumi.get(self, "name") @name.setter def name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "name", value) @property @pulumi.getter def namespaces(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: """ A list of namespaces that limit what we query from CloudWatch """ return pulumi.get(self, "namespaces") @namespaces.setter def namespaces(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "namespaces", value) @property @pulumi.getter(name="pointTagFilterRegex") def point_tag_filter_regex(self) -> Optional[pulumi.Input[str]]: """ A regular expression that AWS tag key name must match (case-insensitively) in order to be ingested """ return pulumi.get(self, "point_tag_filter_regex") @point_tag_filter_regex.setter def point_tag_filter_regex(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "point_tag_filter_regex", value) @property @pulumi.getter(name="serviceRefreshRateInMinutes") def service_refresh_rate_in_minutes(self) -> Optional[pulumi.Input[int]]: """ How often, in minutes, to refresh the service """ return pulumi.get(self, "service_refresh_rate_in_minutes") @service_refresh_rate_in_minutes.setter def service_refresh_rate_in_minutes(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "service_refresh_rate_in_minutes", value) @property @pulumi.getter(name="volumeSelectionTags") def volume_selection_tags(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]: """ A string->string map of whitelist of volume tag-value pairs (in AWS). If the volume's AWS tags match this whitelist, CloudWatch data about this volume is ingested. Multiple entries are OR'ed """ return pulumi.get(self, "volume_selection_tags") @volume_selection_tags.setter def volume_selection_tags(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]): pulumi.set(self, "volume_selection_tags", value) @pulumi.input_type class _CloudIntegrationCloudWatchState: def __init__(__self__, *, additional_tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, external_id: Optional[pulumi.Input[str]] = None, force_save: Optional[pulumi.Input[bool]] = None, instance_selection_tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, metric_filter_regex: Optional[pulumi.Input[str]] = None, name: Optional[pulumi.Input[str]] = None, namespaces: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, point_tag_filter_regex: Optional[pulumi.Input[str]] = None, role_arn: Optional[pulumi.Input[str]] = None, service: Optional[pulumi.Input[str]] = None, service_refresh_rate_in_minutes: Optional[pulumi.Input[int]] = None, volume_selection_tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None): """ Input properties used for looking up and filtering CloudIntegrationCloudWatch resources. :param pulumi.Input[Mapping[str, pulumi.Input[str]]] additional_tags: A list of point tag key-values to add to every point ingested using this integration :param pulumi.Input[str] external_id: The Role ARN that the customer has created in AWS IAM to allow access to Wavefront :param pulumi.Input[bool] force_save: Forces this resource to save, even if errors are present :param pulumi.Input[Mapping[str, pulumi.Input[str]]] instance_selection_tags: A string->string map whitelist of instance tag-value pairs (in AWS). If the instance's AWS tags match this whitelist, CloudWatch data about this instance is ingested. Multiple entries are OR'ed :param pulumi.Input[str] metric_filter_regex: A regular expression that a CloudWatch metric name must match (case-insensitively) in order to be ingested :param pulumi.Input[str] name: The human-readable name of this integration :param pulumi.Input[Sequence[pulumi.Input[str]]] namespaces: A list of namespaces that limit what we query from CloudWatch :param pulumi.Input[str] point_tag_filter_regex: A regular expression that AWS tag key name must match (case-insensitively) in order to be ingested :param pulumi.Input[str] role_arn: The external id corresponding to the Role ARN :param pulumi.Input[str] service: A value denoting which cloud service this service integrates with :param pulumi.Input[int] service_refresh_rate_in_minutes: How often, in minutes, to refresh the service :param pulumi.Input[Mapping[str, pulumi.Input[str]]] volume_selection_tags: A string->string map of whitelist of volume tag-value pairs (in AWS). If the volume's AWS tags match this whitelist, CloudWatch data about this volume is ingested. Multiple entries are OR'ed """ if additional_tags is not None: pulumi.set(__self__, "additional_tags", additional_tags) if external_id is not None: pulumi.set(__self__, "external_id", external_id) if force_save is not None: pulumi.set(__self__, "force_save", force_save) if instance_selection_tags is not None: pulumi.set(__self__, "instance_selection_tags", instance_selection_tags) if metric_filter_regex is not None: pulumi.set(__self__, "metric_filter_regex", metric_filter_regex) if name is not None: pulumi.set(__self__, "name", name) if namespaces is not None: pulumi.set(__self__, "namespaces", namespaces) if point_tag_filter_regex is not None: pulumi.set(__self__, "point_tag_filter_regex", point_tag_filter_regex) if role_arn is not None: pulumi.set(__self__, "role_arn", role_arn) if service is not None: pulumi.set(__self__, "service", service) if service_refresh_rate_in_minutes is not None: pulumi.set(__self__, "service_refresh_rate_in_minutes", service_refresh_rate_in_minutes) if volume_selection_tags is not None: pulumi.set(__self__, "volume_selection_tags", volume_selection_tags) @property @pulumi.getter(name="additionalTags") def additional_tags(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]: """ A list of point tag key-values to add to every point ingested using this integration """ return pulumi.get(self, "additional_tags") @additional_tags.setter def additional_tags(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]): pulumi.set(self, "additional_tags", value) @property @pulumi.getter(name="externalId") def external_id(self) -> Optional[pulumi.Input[str]]: """ The Role ARN that the customer has created in AWS IAM to allow access to Wavefront """ return pulumi.get(self, "external_id") @external_id.setter def external_id(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "external_id", value) @property @pulumi.getter(name="forceSave") def force_save(self) -> Optional[pulumi.Input[bool]]: """ Forces this resource to save, even if errors are present """ return pulumi.get(self, "force_save") @force_save.setter def force_save(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "force_save", value) @property @pulumi.getter(name="instanceSelectionTags") def instance_selection_tags(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]: """ A string->string map whitelist of instance tag-value pairs (in AWS). If the instance's AWS tags match this whitelist, CloudWatch data about this instance is ingested. Multiple entries are OR'ed """ return pulumi.get(self, "instance_selection_tags") @instance_selection_tags.setter def instance_selection_tags(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]): pulumi.set(self, "instance_selection_tags", value) @property @pulumi.getter(name="metricFilterRegex") def metric_filter_regex(self) -> Optional[pulumi.Input[str]]: """ A regular expression that a CloudWatch metric name must match (case-insensitively) in order to be ingested """ return pulumi.get(self, "metric_filter_regex") @metric_filter_regex.setter def metric_filter_regex(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "metric_filter_regex", value) @property @pulumi.getter def name(self) -> Optional[pulumi.Input[str]]: """ The human-readable name of this integration """ return pulumi.get(self, "name") @name.setter def name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "name", value) @property @pulumi.getter def namespaces(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: """ A list of namespaces that limit what we query from CloudWatch """ return pulumi.get(self, "namespaces") @namespaces.setter def namespaces(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "namespaces", value) @property @pulumi.getter(name="pointTagFilterRegex") def point_tag_filter_regex(self) -> Optional[pulumi.Input[str]]: """ A regular expression that AWS tag key name must match (case-insensitively) in order to be ingested """ return pulumi.get(self, "point_tag_filter_regex") @point_tag_filter_regex.setter def point_tag_filter_regex(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "point_tag_filter_regex", value) @property @pulumi.getter(name="roleArn") def role_arn(self) -> Optional[pulumi.Input[str]]: """ The external id corresponding to the Role ARN """ return pulumi.get(self, "role_arn") @role_arn.setter def role_arn(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "role_arn", value) @property @pulumi.getter def service(self) -> Optional[pulumi.Input[str]]: """ A value denoting which cloud service this service integrates with """ return pulumi.get(self, "service") @service.setter def service(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "service", value) @property @pulumi.getter(name="serviceRefreshRateInMinutes") def service_refresh_rate_in_minutes(self) -> Optional[pulumi.Input[int]]: """ How often, in minutes, to refresh the service """ return pulumi.get(self, "service_refresh_rate_in_minutes") @service_refresh_rate_in_minutes.setter def service_refresh_rate_in_minutes(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "service_refresh_rate_in_minutes", value) @property @pulumi.getter(name="volumeSelectionTags") def volume_selection_tags(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]: """ A string->string map of whitelist of volume tag-value pairs (in AWS). If the volume's AWS tags match this whitelist, CloudWatch data about this volume is ingested. Multiple entries are OR'ed """ return pulumi.get(self, "volume_selection_tags") @volume_selection_tags.setter def volume_selection_tags(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]): pulumi.set(self, "volume_selection_tags", value) class CloudIntegrationCloudWatch(pulumi.CustomResource): @overload def __init__(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, additional_tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, external_id: Optional[pulumi.Input[str]] = None, force_save: Optional[pulumi.Input[bool]] = None, instance_selection_tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, metric_filter_regex: Optional[pulumi.Input[str]] = None, name: Optional[pulumi.Input[str]] = None, namespaces: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, point_tag_filter_regex: Optional[pulumi.Input[str]] = None, role_arn: Optional[pulumi.Input[str]] = None, service: Optional[pulumi.Input[str]] = None, service_refresh_rate_in_minutes: Optional[pulumi.Input[int]] = None, volume_selection_tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, __props__=None): """ Provides a Wavefront Cloud Integration for CloudTrail. This allows CloudTrail cloud integrations to be created, updated, and delete ## Example Usage ```python import pulumi import pulumi_wavefront as wavefront ext_id = wavefront.CloudIntegrationAwsExternalId("extId") cloudwatch = wavefront.CloudIntegrationCloudWatch("cloudwatch", force_save=True, role_arn="arn:aws::1234567:role/example-arn", external_id=ext_id.id) ``` ## Import CloudWatch Cloud Integrations can be imported using the `id`, e.g. ```sh $ pulumi import wavefront:index/cloudIntegrationCloudWatch:CloudIntegrationCloudWatch cloudwatch a411c16b-3cf7-4f03-bf11-8ca05aab898d ``` :param str resource_name: The name of the resource. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[Mapping[str, pulumi.Input[str]]] additional_tags: A list of point tag key-values to add to every point ingested using this integration :param pulumi.Input[str] external_id: The Role ARN that the customer has created in AWS IAM to allow access to Wavefront :param pulumi.Input[bool] force_save: Forces this resource to save, even if errors are present :param pulumi.Input[Mapping[str, pulumi.Input[str]]] instance_selection_tags: A string->string map whitelist of instance tag-value pairs (in AWS). If the instance's AWS tags match this whitelist, CloudWatch data about this instance is ingested. Multiple entries are OR'ed :param pulumi.Input[str] metric_filter_regex: A regular expression that a CloudWatch metric name must match (case-insensitively) in order to be ingested :param pulumi.Input[str] name: The human-readable name of this integration :param pulumi.Input[Sequence[pulumi.Input[str]]] namespaces: A list of namespaces that limit what we query from CloudWatch :param pulumi.Input[str] point_tag_filter_regex: A regular expression that AWS tag key name must match (case-insensitively) in order to be ingested :param pulumi.Input[str] role_arn: The external id corresponding to the Role ARN :param pulumi.Input[str] service: A value denoting which cloud service this service integrates with :param pulumi.Input[int] service_refresh_rate_in_minutes: How often, in minutes, to refresh the service :param pulumi.Input[Mapping[str, pulumi.Input[str]]] volume_selection_tags: A string->string map of whitelist of volume tag-value pairs (in AWS). If the volume's AWS tags match this whitelist, CloudWatch data about this volume is ingested. Multiple entries are OR'ed """ ... @overload def __init__(__self__, resource_name: str, args: CloudIntegrationCloudWatchArgs, opts: Optional[pulumi.ResourceOptions] = None): """ Provides a Wavefront Cloud Integration for CloudTrail. This allows CloudTrail cloud integrations to be created, updated, and delete ## Example Usage ```python import pulumi import pulumi_wavefront as wavefront ext_id = wavefront.CloudIntegrationAwsExternalId("extId") cloudwatch = wavefront.CloudIntegrationCloudWatch("cloudwatch", force_save=True, role_arn="arn:aws::1234567:role/example-arn", external_id=ext_id.id) ``` ## Import CloudWatch Cloud Integrations can be imported using the `id`, e.g. ```sh $ pulumi import wavefront:index/cloudIntegrationCloudWatch:CloudIntegrationCloudWatch cloudwatch a411c16b-3cf7-4f03-bf11-8ca05aab898d ``` :param str resource_name: The name of the resource. :param CloudIntegrationCloudWatchArgs args: The arguments to use to populate this resource's properties. :param pulumi.ResourceOptions opts: Options for the resource. """ ... def __init__(__self__, resource_name: str, *args, **kwargs): resource_args, opts = _utilities.get_resource_args_opts(CloudIntegrationCloudWatchArgs, pulumi.ResourceOptions, *args, **kwargs) if resource_args is not None: __self__._internal_init(resource_name, opts, **resource_args.__dict__) else: __self__._internal_init(resource_name, *args, **kwargs) def _internal_init(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, additional_tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, external_id: Optional[pulumi.Input[str]] = None, force_save: Optional[pulumi.Input[bool]] = None, instance_selection_tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, metric_filter_regex: Optional[pulumi.Input[str]] = None, name: Optional[pulumi.Input[str]] = None, namespaces: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, point_tag_filter_regex: Optional[pulumi.Input[str]] = None, role_arn: Optional[pulumi.Input[str]] = None, service: Optional[pulumi.Input[str]] = None, service_refresh_rate_in_minutes: Optional[pulumi.Input[int]] = None, volume_selection_tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, __props__=None): if opts is None: opts = pulumi.ResourceOptions() if not isinstance(opts, pulumi.ResourceOptions): raise TypeError('Expected resource options to be a ResourceOptions instance') if opts.version is None: opts.version = _utilities.get_version() if opts.id is None: if __props__ is not None: raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource') __props__ = CloudIntegrationCloudWatchArgs.__new__(CloudIntegrationCloudWatchArgs) __props__.__dict__["additional_tags"] = additional_tags if external_id is None and not opts.urn: raise TypeError("Missing required property 'external_id'") __props__.__dict__["external_id"] = external_id __props__.__dict__["force_save"] = force_save __props__.__dict__["instance_selection_tags"] = instance_selection_tags __props__.__dict__["metric_filter_regex"] = metric_filter_regex __props__.__dict__["name"] = name __props__.__dict__["namespaces"] = namespaces __props__.__dict__["point_tag_filter_regex"] = point_tag_filter_regex if role_arn is None and not opts.urn: raise TypeError("Missing required property 'role_arn'") __props__.__dict__["role_arn"] = role_arn if service is None and not opts.urn: raise TypeError("Missing required property 'service'") __props__.__dict__["service"] = service __props__.__dict__["service_refresh_rate_in_minutes"] = service_refresh_rate_in_minutes __props__.__dict__["volume_selection_tags"] = volume_selection_tags super(CloudIntegrationCloudWatch, __self__).__init__( 'wavefront:index/cloudIntegrationCloudWatch:CloudIntegrationCloudWatch', resource_name, __props__, opts) @staticmethod def get(resource_name: str, id: pulumi.Input[str], opts: Optional[pulumi.ResourceOptions] = None, additional_tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, external_id: Optional[pulumi.Input[str]] = None, force_save: Optional[pulumi.Input[bool]] = None, instance_selection_tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, metric_filter_regex: Optional[pulumi.Input[str]] = None, name: Optional[pulumi.Input[str]] = None, namespaces: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, point_tag_filter_regex: Optional[pulumi.Input[str]] = None, role_arn: Optional[pulumi.Input[str]] = None, service: Optional[pulumi.Input[str]] = None, service_refresh_rate_in_minutes: Optional[pulumi.Input[int]] = None, volume_selection_tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None) -> 'CloudIntegrationCloudWatch': """ Get an existing CloudIntegrationCloudWatch resource's state with the given name, id, and optional extra properties used to qualify the lookup. :param str resource_name: The unique name of the resulting resource. :param pulumi.Input[str] id: The unique provider ID of the resource to lookup. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[Mapping[str, pulumi.Input[str]]] additional_tags: A list of point tag key-values to add to every point ingested using this integration :param pulumi.Input[str] external_id: The Role ARN that the customer has created in AWS IAM to allow access to Wavefront :param pulumi.Input[bool] force_save: Forces this resource to save, even if errors are present :param pulumi.Input[Mapping[str, pulumi.Input[str]]] instance_selection_tags: A string->string map whitelist of instance tag-value pairs (in AWS). If the instance's AWS tags match this whitelist, CloudWatch data about this instance is ingested. Multiple entries are OR'ed :param pulumi.Input[str] metric_filter_regex: A regular expression that a CloudWatch metric name must match (case-insensitively) in order to be ingested :param pulumi.Input[str] name: The human-readable name of this integration :param pulumi.Input[Sequence[pulumi.Input[str]]] namespaces: A list of namespaces that limit what we query from CloudWatch :param pulumi.Input[str] point_tag_filter_regex: A regular expression that AWS tag key name must match (case-insensitively) in order to be ingested :param pulumi.Input[str] role_arn: The external id corresponding to the Role ARN :param pulumi.Input[str] service: A value denoting which cloud service this service integrates with :param pulumi.Input[int] service_refresh_rate_in_minutes: How often, in minutes, to refresh the service :param pulumi.Input[Mapping[str, pulumi.Input[str]]] volume_selection_tags: A string->string map of whitelist of volume tag-value pairs (in AWS). If the volume's AWS tags match this whitelist, CloudWatch data about this volume is ingested. Multiple entries are OR'ed """ opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id)) __props__ = _CloudIntegrationCloudWatchState.__new__(_CloudIntegrationCloudWatchState) __props__.__dict__["additional_tags"] = additional_tags __props__.__dict__["external_id"] = external_id __props__.__dict__["force_save"] = force_save __props__.__dict__["instance_selection_tags"] = instance_selection_tags __props__.__dict__["metric_filter_regex"] = metric_filter_regex __props__.__dict__["name"] = name __props__.__dict__["namespaces"] = namespaces __props__.__dict__["point_tag_filter_regex"] = point_tag_filter_regex __props__.__dict__["role_arn"] = role_arn __props__.__dict__["service"] = service __props__.__dict__["service_refresh_rate_in_minutes"] = service_refresh_rate_in_minutes __props__.__dict__["volume_selection_tags"] = volume_selection_tags return CloudIntegrationCloudWatch(resource_name, opts=opts, __props__=__props__) @property @pulumi.getter(name="additionalTags") def additional_tags(self) -> pulumi.Output[Optional[Mapping[str, str]]]: """ A list of point tag key-values to add to every point ingested using this integration """ return pulumi.get(self, "additional_tags") @property @pulumi.getter(name="externalId") def external_id(self) -> pulumi.Output[str]: """ The Role ARN that the customer has created in AWS IAM to allow access to Wavefront """ return pulumi.get(self, "external_id") @property @pulumi.getter(name="forceSave") def force_save(self) -> pulumi.Output[Optional[bool]]: """ Forces this resource to save, even if errors are present """ return pulumi.get(self, "force_save") @property @pulumi.getter(name="instanceSelectionTags") def instance_selection_tags(self) -> pulumi.Output[Optional[Mapping[str, str]]]: """ A string->string map whitelist of instance tag-value pairs (in AWS). If the instance's AWS tags match this whitelist, CloudWatch data about this instance is ingested. Multiple entries are OR'ed """ return pulumi.get(self, "instance_selection_tags") @property @pulumi.getter(name="metricFilterRegex") def metric_filter_regex(self) -> pulumi.Output[Optional[str]]: """ A regular expression that a CloudWatch metric name must match (case-insensitively) in order to be ingested """ return pulumi.get(self, "metric_filter_regex") @property @pulumi.getter def name(self) -> pulumi.Output[str]: """ The human-readable name of this integration """ return pulumi.get(self, "name") @property @pulumi.getter def namespaces(self) -> pulumi.Output[Optional[Sequence[str]]]: """ A list of namespaces that limit what we query from CloudWatch """ return pulumi.get(self, "namespaces") @property @pulumi.getter(name="pointTagFilterRegex") def point_tag_filter_regex(self) -> pulumi.Output[Optional[str]]: """ A regular expression that AWS tag key name must match (case-insensitively) in order to be ingested """ return pulumi.get(self, "point_tag_filter_regex") @property @pulumi.getter(name="roleArn") def role_arn(self) -> pulumi.Output[str]: """ The external id corresponding to the Role ARN """ return pulumi.get(self, "role_arn") @property @pulumi.getter def service(self) -> pulumi.Output[str]: """ A value denoting which cloud service this service integrates with """ return pulumi.get(self, "service") @property @pulumi.getter(name="serviceRefreshRateInMinutes") def service_refresh_rate_in_minutes(self) -> pulumi.Output[Optional[int]]: """ How often, in minutes, to refresh the service """ return pulumi.get(self, "service_refresh_rate_in_minutes") @property @pulumi.getter(name="volumeSelectionTags") def volume_selection_tags(self) -> pulumi.Output[Optional[Mapping[str, str]]]: """ A string->string map of whitelist of volume tag-value pairs (in AWS). If the volume's AWS tags match this whitelist, CloudWatch data about this volume is ingested. Multiple entries are OR'ed """ return pulumi.get(self, "volume_selection_tags")

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0.098931

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null

0

8

e340cde71ee057dc6b96040f9effca6903ab6a1a

164

py

Python

anti_sybil/algorithms/__init__.py

abramsymons/BrightID-AntiSybil

86161afe654f46475944ebdb3b5453a1723180d9

[ "ISC" ]

null

anti_sybil/algorithms/__init__.py

abramsymons/BrightID-AntiSybil

86161afe654f46475944ebdb3b5453a1723180d9

[ "ISC" ]

null

anti_sybil/algorithms/__init__.py

abramsymons/BrightID-AntiSybil

86161afe654f46475944ebdb3b5453a1723180d9

[ "ISC" ]

1

2020-03-28T05:05:19.000Z

from group_sybil_rank import GroupSybilRank from sybil_rank import SybilRank from group_merging import GroupMergingRank from sybil_group_rank import SybilGroupRank

32.8

43

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8b5d7c9781c2a6b0babd87d3ac8a5059f9f5f1e9

5,079

py

Python

tests/unit/utils/wrappers/aws/test_api_gateway.py

HathorNetwork/hathor-explorer-service

81236deceac12ddfd813b33723481421a9064c82

[ "MIT" ]

null

tests/unit/utils/wrappers/aws/test_api_gateway.py

HathorNetwork/hathor-explorer-service

81236deceac12ddfd813b33723481421a9064c82

[ "MIT" ]

51

2021-05-21T18:58:15.000Z

2022-03-29T17:45:00.000Z

tests/unit/utils/wrappers/aws/test_api_gateway.py

HathorNetwork/hathor-explorer-service

81236deceac12ddfd813b33723481421a9064c82

[ "MIT" ]

1

2022-02-08T21:15:26.000Z

from unittest.mock import MagicMock, patch from aws_lambda_context import LambdaContext from common.errors import ApiError from utils.wrappers.aws.api_gateway import ApiGateway class TestApiGateway: def test_calling_function(self): function = MagicMock(return_value={'statusCode': 200, 'headers': {}}) api_gateway = ApiGateway() event = { 'body': '{}', 'headers': {} } context = LambdaContext() result = api_gateway.__call__(function)(event, context) function.assert_called() assert result['statusCode'] == 200 def test_returning_error(self): function = MagicMock(side_effect=ApiError('not_authorized')) api_gateway = ApiGateway() event = { 'body': '{}', 'headers': {} } context = LambdaContext() result = api_gateway.__call__(function)(event, context) function.assert_called() assert result['statusCode'] == 401 def test_return_500_on_unkown_apierror(self): function = MagicMock(side_effect=ApiError('Boom!')) api_gateway = ApiGateway() event = { 'body': '{}', 'headers': {} } context = LambdaContext() result = api_gateway.__call__(function)(event, context) function.assert_called() assert result['statusCode'] == 500 assert result['body'] == '{"error": "Boom!"}' def test_return_500_on_unkown_exception(self): function = MagicMock(side_effect=Exception('Boom!')) api_gateway = ApiGateway() event = { 'body': '{}', 'headers': {} } context = LambdaContext() result = api_gateway.__call__(function)(event, context) function.assert_called() assert result['statusCode'] == 500 assert result['body'] == '{"error": "Boom!"}' def test_parse_json_fail_proof(self): function = MagicMock(return_value={'statusCode': 200, 'headers': {}}) api_gateway = ApiGateway() event = { 'body': 'bad-json-value', 'headers': {} } context = LambdaContext() result = api_gateway.__call__(function)(event, context) function.assert_called() assert result['statusCode'] == 200 @patch('utils.wrappers.aws.api_gateway.CORS_ALLOWED_ORIGIN', 'explorer.hathor.network') def test_returning_cors_headers(self): function = MagicMock(return_value={'statusCode': 200, 'headers': {}}) api_gateway = ApiGateway() event = { 'body': '{}', 'headers': {} } context = LambdaContext() result = api_gateway.__call__(function)(event, context) function.assert_called() assert result['headers']['Access-Control-Allow-Origin'] assert result['headers']['Access-Control-Allow-Credentials'] @patch('utils.wrappers.aws.api_gateway.CORS_ALLOWED_ORIGIN', 'explorer.hathor.network') def test_returning_cors_on_apierror(self): function = MagicMock(side_effect=ApiError('Boom!')) api_gateway = ApiGateway() event = { 'body': '{}', 'headers': {} } context = LambdaContext() result = api_gateway.__call__(function)(event, context) function.assert_called() assert result['headers']['Access-Control-Allow-Origin'] assert result['headers']['Access-Control-Allow-Credentials'] @patch('utils.wrappers.aws.api_gateway.CORS_ALLOWED_ORIGIN', 'explorer.hathor.network') def test_returning_cors_on_error(self): function = MagicMock(side_effect=Exception('Boom!')) api_gateway = ApiGateway() event = { 'body': '{}', 'headers': {} } context = LambdaContext() result = api_gateway.__call__(function)(event, context) function.assert_called() assert result['headers']['Access-Control-Allow-Origin'] assert result['headers']['Access-Control-Allow-Credentials'] @patch('utils.wrappers.aws.api_gateway.CORS_ALLOWED_ORIGIN', 'explorer.hathor.network') def test_works_with_no_headers_from_function(self): function = MagicMock(return_value={'statusCode': 200}) api_gateway = ApiGateway() event = { 'body': '{}', 'headers': {} } context = LambdaContext() result = api_gateway.__call__(function)(event, context) function.assert_called() assert result['headers'] @patch('utils.wrappers.aws.api_gateway.CORS_ALLOWED_ORIGIN', None) def test_no_headers_with_no_config(self): function = MagicMock(return_value={'statusCode': 200}) api_gateway = ApiGateway() event = { 'body': '{}', 'headers': {} } context = LambdaContext() result = api_gateway.__call__(function)(event, context) function.assert_called() assert result['headers'] == {}

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5,079

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0.089347

0.072165

0.085911

0.900344

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0.854983

0.838488

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5,079

177

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28.694915

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0

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0

0.2

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0.08

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null

0

1

0

1

0

null

0

7

8b702ab7a37dfb5a73cd9894f626476d0ac2a8e2

1,994

py

Python

hours/migrations/0010_add_ancestry_fields_to_resource.py

SuviVappula/hauki

1af20d3a2e6fd7f7ca2834aaa52d3355aa658dfb

[ "MIT" ]

3

2020-03-26T05:04:30.000Z

2022-03-22T15:57:18.000Z

hours/migrations/0010_add_ancestry_fields_to_resource.py

SuviVappula/hauki

1af20d3a2e6fd7f7ca2834aaa52d3355aa658dfb

[ "MIT" ]

81

2020-06-17T14:31:11.000Z

2022-02-20T19:01:54.000Z

hours/migrations/0010_add_ancestry_fields_to_resource.py

SuviVappula/hauki

1af20d3a2e6fd7f7ca2834aaa52d3355aa658dfb

[ "MIT" ]

9

2020-06-18T10:52:09.000Z

2022-02-11T13:05:59.000Z

# Generated by Django 3.1.2 on 2020-11-27 12:40 import django.contrib.postgres.fields from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ("hours", "0009_merge_20201126_1559"), ] operations = [ migrations.AddField( model_name="historicalresource", name="ancestry_data_source", field=django.contrib.postgres.fields.ArrayField( base_field=models.CharField(max_length=255), blank=True, null=True, size=None, ), ), migrations.AddField( model_name="historicalresource", name="ancestry_is_public", field=models.BooleanField(blank=True, null=True), ), migrations.AddField( model_name="historicalresource", name="ancestry_organization", field=django.contrib.postgres.fields.ArrayField( base_field=models.CharField(max_length=255), blank=True, null=True, size=None, ), ), migrations.AddField( model_name="resource", name="ancestry_data_source", field=django.contrib.postgres.fields.ArrayField( base_field=models.CharField(max_length=255), blank=True, null=True, size=None, ), ), migrations.AddField( model_name="resource", name="ancestry_is_public", field=models.BooleanField(blank=True, null=True), ), migrations.AddField( model_name="resource", name="ancestry_organization", field=django.contrib.postgres.fields.ArrayField( base_field=models.CharField(max_length=255), blank=True, null=True, size=None, ), ), ]

30.676923

61

0.538114

176

1,994

5.943182

0.301136

0.10325

0.131931

0.154876

0.826004

0.740918

0

0.033858

0.363089

1,994

64

62

31.15625

0.789764

0.022568

0

0.862069

1

0

0.115562

0.033898

0

1

0

false

0

0.034483

0

0.086207

0

null

0

1

0

1

0

null

0

8

8b82b95fd22827d36fb95f44c7310b38025b135e

4,838

py

Python

aion/cores/hard_cores/_font_rom.py

Sketch98/aion

0aec424dbebc77032ca135093a13eb97bdaec0b7

[ "MIT" ]

null

aion/cores/hard_cores/_font_rom.py

Sketch98/aion

0aec424dbebc77032ca135093a13eb97bdaec0b7

[ "MIT" ]

null

aion/cores/hard_cores/_font_rom.py

Sketch98/aion

0aec424dbebc77032ca135093a13eb97bdaec0b7

[ "MIT" ]

null

from myhdl import always, block @block def font_rom(font_size, name, rom_port): font_roms = { (4, 6): font_rom_4x6, (5, 12): font_rom_5x12, (7, 12): font_rom_7x12, (8, 12): font_rom_8x12, (10, 18): font_rom_10x18, (12, 16): font_rom_12x16 } assert font_size in font_roms, 'font size {} is not supported.\n' \ 'supported font sizes are \n' \ '{}'.format(font_size, font_roms.keys()) return font_roms[font_size](name, rom_port.clk, rom_port.addr, rom_port.data) @block def font_rom_4x6(name, clk, addr, data): @always(clk) def foo(): pass assert len(addr) == 10, 'addr width = {}, should be 10'.format(len(addr)) assert len(data) == 4, 'data width = {}, should be 4'.format(len(data)) clk.read = True addr.read = True data.driven = True return foo font_rom_4x6.vhdl_code = \ """ --copy this signal declaration to architecture declaration signal ${data}_slv : std_logic_vector(3 downto 0); ${data} <= unsigned(${data}_slv); $name: entity work.font_rom_4x6 port map ( clka => $clk, addra => std_logic_vector($addr), douta => ${data}_slv); """ @block def font_rom_5x12(name, clk, addr, data): @always(clk) def foo(): pass assert len(addr) == 11, 'addr width = {}, should be 11'.format(len(addr)) assert len(data) == 5, 'data width = {}, should be 5'.format(len(data)) clk.read = True addr.read = True data.driven = True return foo font_rom_5x12.vhdl_code = \ """ --copy this signal declaration to architecture declaration signal ${data}_slv : std_logic_vector(4 downto 0); ${data} <= unsigned(${data}_slv); $name: entity work.font_rom_5x12 port map ( clka => $clk, addra => std_logic_vector($addr), douta => ${data}_slv); """ @block def font_rom_7x12(name, clk, addr, data): @always(clk) def foo(): pass assert len(addr) == 11, 'addr width = {}, should be 11'.format(len(addr)) assert len(data) == 7, 'data width = {}, should be 7'.format(len(data)) clk.read = True addr.read = True data.driven = True return foo font_rom_7x12.vhdl_code = \ """ --copy this signal declaration to architecture declaration signal ${data}_slv : std_logic_vector(6 downto 0); ${data} <= unsigned(${data}_slv); $name: entity work.font_rom_7x12 port map ( clka => $clk, addra => std_logic_vector($addr), douta => ${data}_slv); """ @block def font_rom_8x12(name, clk, addr, data): @always(clk) def foo(): pass assert len(addr) == 11, 'addr width = {}, should be 11'.format(len(addr)) assert len(data) == 8, 'data width = {}, should be 8'.format(len(data)) clk.read = True addr.read = True data.driven = True return foo font_rom_8x12.vhdl_code = \ """ --copy this signal declaration to architecture declaration signal ${data}_slv : std_logic_vector(7 downto 0); ${data} <= unsigned(${data}_slv); $name: entity work.font_rom_8x12 port map ( clka => $clk, addra => std_logic_vector($addr), douta => ${data}_slv); """ @block def font_rom_10x18(name, clk, addr, data): @always(clk) def foo(): pass assert len(addr) == 12, 'addr width = {}, should be 12'.format(len(addr)) assert len(data) == 10, 'data width = {}, should be 8'.format(len(data)) clk.read = True addr.read = True data.driven = True return foo font_rom_10x18.vhdl_code = \ """ --copy this signal declaration to architecture declaration signal ${data}_slv : std_logic_vector(9 downto 0); ${data} <= unsigned(${data}_slv); $name: entity work.font_rom_10x18 port map ( clka => $clk, addra => std_logic_vector($addr), douta => ${data}_slv); """ @block def font_rom_12x16(name, clk, addr, data): @always(clk) def foo(): pass assert len(addr) == 11, 'addr width = {}, should be 11'.format(len(addr)) assert len(data) == 12, 'data width = {}, should be 12'.format(len(data)) clk.read = True addr.read = True data.driven = True return foo font_rom_12x16.vhdl_code = \ """ --copy this signal declaration to architecture declaration signal ${data}_slv : std_logic_vector(11 downto 0); ${data} <= unsigned(${data}_slv); $name: entity work.font_rom_12x16 port map ( clka => $clk, addra => std_logic_vector($addr), douta => ${data}_slv); """

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8b9053f3b3651cce336073734885a7f8a8d5d097

200

py

Python

userelaina/th.py

userElaina/sugar

fc1493c79b66a5609fd268e14b9407edef6a3b10

[ "MIT" ]

1

2021-06-23T04:09:31.000Z

userelaina/th.py

userElaina/sugar

fc1493c79b66a5609fd268e14b9407edef6a3b10

[ "MIT" ]

null

userelaina/th.py

userElaina/sugar

fc1493c79b66a5609fd268e14b9407edef6a3b10

[ "MIT" ]

null

''' `throws` `nThread` `getlock` `lock` `unlock` >>> throws(f:function,args=tuple()) >>> nThread(n=16,clk=0,f=None) ''' from userelaina._th import throws,nThread,getlock,lock,unlock

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8bb5ddd1eedcd2727d313429757d1dbe9da981dc

27,386

py

Python

app/openlxp_xia/tests/test_xia_command_intergration.py

OpenLXP/openlxp-xia

5c71b8d5028562d596ab738b72562118efcbefba

[ "Apache-2.0" ]

null

app/openlxp_xia/tests/test_xia_command_intergration.py

OpenLXP/openlxp-xia

5c71b8d5028562d596ab738b72562118efcbefba

[ "Apache-2.0" ]

3

2020-12-15T18:33:56.000Z

2022-03-09T19:43:41.000Z

app/openlxp_xia/tests/test_xia_command_intergration.py

OpenLXP/openlxp-xia

5c71b8d5028562d596ab738b72562118efcbefba

[ "Apache-2.0" ]

null

import logging from unittest.mock import patch from ddt import ddt from django.test import tag from django.utils import timezone from openlxp_xia.management.commands.load_target_metadata import ( post_data_to_xis, rename_metadata_ledger_fields) from openlxp_xia.management.commands.transform_source_metadata import ( store_transformed_source_metadata, transform_source_using_key) from openlxp_xia.management.commands.validate_source_metadata import ( get_source_metadata_for_validation, store_source_metadata_validation_status, validate_source_using_key) from openlxp_xia.management.commands.validate_target_metadata import ( get_target_validation_schema, store_target_metadata_validation_status, validate_target_using_key) from openlxp_xia.management.utils.xss_client import read_json_data from openlxp_xia.models import (MetadataFieldOverwrite, MetadataLedger, SupplementalLedger, XIAConfiguration, XISConfiguration) from .test_setup import TestSetUp logger = logging.getLogger('dict_config_logger') @tag('integration') @ddt class CommandIntegration(TestSetUp): # globally accessible data sets # Test cases for validate_source_metadata def test_get_source_metadata_for_validation(self): """Test retrieving source metadata from MetadataLedger that needs to be validated""" metadata_ledger = MetadataLedger( record_lifecycle_status='Active', source_metadata=self.source_metadata, source_metadata_hash=self.hash_value, source_metadata_key=self.key_value, source_metadata_key_hash=self.key_value_hash, source_metadata_extraction_date=timezone.now()) metadata_ledger.save() test_source_data = get_source_metadata_for_validation() self.assertTrue(test_source_data) def test_validate_source_using_key(self): """Test to check validation process for source""" recommended_column_name = [] metadata_ledger = MetadataLedger( record_lifecycle_status='Active', source_metadata=self.source_metadata, source_metadata_hash=self.hash_value, source_metadata_key=self.key_value, source_metadata_key_hash=self.key_value_hash, source_metadata_extraction_date=timezone.now()) metadata_ledger_invalid = MetadataLedger( record_lifecycle_status='Active', source_metadata=self.metadata_invalid, source_metadata_hash=self.hash_value_invalid, source_metadata_key=self.key_value_invalid, source_metadata_key_hash=self.key_value_hash_invalid, source_metadata_extraction_date=timezone.now()) metadata_ledger.save() metadata_ledger_invalid.save() result_test_query = MetadataLedger.objects. \ values('source_metadata_key_hash', 'source_metadata') validate_source_using_key(result_test_query, self.test_required_column_names, recommended_column_name) result_query = MetadataLedger.objects. \ values('source_metadata_validation_status', 'record_lifecycle_status'). \ filter(source_metadata_key=self.key_value).first() result_query_invalid = MetadataLedger.objects. \ values('source_metadata_validation_status', 'record_lifecycle_status'). \ filter(source_metadata_key=self.key_value_invalid).first() self.assertEqual('Y', result_query['source_metadata_validation_status']) self.assertEqual('Active', result_query['record_lifecycle_status']) self.assertEqual('N', result_query_invalid[ 'source_metadata_validation_status']) def test_store_source_metadata_validation_status_valid(self): """Test to store validation status for valid source metadata in metadata ledger """ metadata_ledger = MetadataLedger( source_metadata=self.source_metadata, source_metadata_key_hash=self.key_value_hash, source_metadata_key=self.key_value) metadata_ledger.save() store_source_metadata_validation_status(MetadataLedger.objects. values('source_metadata'), self.key_value_hash, 'Y', 'Active', MetadataLedger.objects. values('source_metadata') ) result_query = MetadataLedger.objects.values( 'source_metadata_validation_status', 'source_metadata_validation_date', 'record_lifecycle_status').filter( source_metadata_key_hash=self.key_value_hash).first() self.assertTrue(result_query.get('source_metadata_validation_date')) self.assertEqual("Y", result_query.get( 'source_metadata_validation_status')) self.assertEqual('Active', result_query.get( 'record_lifecycle_status')) def test_store_source_metadata_validation_status_invalid(self): """Test to store validation status for invalid source metadata in metadata ledger """ metadata_ledger = MetadataLedger( source_metadata=self.source_metadata, source_metadata_key_hash=self.key_value_hash, source_metadata_key=self.key_value) metadata_ledger.save() store_source_metadata_validation_status(MetadataLedger.objects. values('source_metadata'), self.key_value_hash, 'N', 'Inactive', MetadataLedger.objects. values('source_metadata') ) result_query = MetadataLedger.objects.values( 'metadata_record_inactivation_date', 'source_metadata_validation_status', 'source_metadata_validation_date', 'record_lifecycle_status').filter( source_metadata_key_hash=self.key_value_hash).first() self.assertTrue(result_query.get('source_metadata_validation_date')) self.assertTrue(result_query.get('metadata_record_inactivation_date')) self.assertEqual("N", result_query.get( 'source_metadata_validation_status')) self.assertEqual('Inactive', result_query.get( 'record_lifecycle_status')) # Test cases for transform_source_metadata def test_transform_source_using_key_overwrite(self): """Test to transform source metadata to target metadata schema format""" metadata_ledger = MetadataLedger( record_lifecycle_status='Active', source_metadata=self.source_metadata_overwrite, source_metadata_key_hash=self.key_value_hash_overwrite, source_metadata_validation_status='Y', source_metadata_key=self.key_value_overwrite, source_metadata_validation_date=timezone.now(), source_metadata_extraction_date=timezone.now()) metadata_ledger.save() test_data_dict = MetadataLedger.objects.values( 'source_metadata').filter( source_metadata_validation_status='Y', record_lifecycle_status='Active').exclude( source_metadata_validation_date=None) test_metadata_overwrite = \ MetadataFieldOverwrite(field_name='test_name', field_type='char', field_value='new_value', overwrite=True) test_metadata_overwrite.save() transform_source_using_key(test_data_dict, self.source_target_mapping, self.test_required_column_names, self.expected_datatype) result_data = MetadataLedger.objects.filter( source_metadata_key=self.key_value_overwrite, record_lifecycle_status='Active', source_metadata_validation_status='Y' ).values( 'source_metadata_transformation_date', 'target_metadata_key', 'target_metadata_key_hash', 'target_metadata', 'target_metadata_hash').first() result_data_supplemental = SupplementalLedger.objects.filter( supplemental_metadata_key=self.key_value_overwrite, record_lifecycle_status='Active', ).values( 'supplemental_metadata_transformation_date', 'supplemental_metadata_key', 'supplemental_metadata_key_hash', 'supplemental_metadata', 'supplemental_metadata_hash').first() self.assertTrue(result_data.get('source_metadata_transformation_date')) self.assertTrue(result_data.get('target_metadata_key')) self.assertTrue(result_data.get('target_metadata_key_hash')) self.assertTrue(result_data.get('target_metadata')) self.assertTrue(result_data.get('target_metadata_hash')) self.assertTrue(result_data_supplemental. get('supplemental_metadata_transformation_date')) self.assertTrue(result_data_supplemental. get('supplemental_metadata_key')) self.assertTrue(result_data_supplemental. get('supplemental_metadata_key_hash')) self.assertTrue(result_data_supplemental. get('supplemental_metadata')) self.assertTrue(result_data_supplemental. get('supplemental_metadata_hash')) def test_transform_source_using_key(self): """Test to transform source metadata to target metadata schema format""" metadata_ledger = MetadataLedger( record_lifecycle_status='Active', source_metadata=self.source_metadata, source_metadata_key_hash=self.key_value_hash, source_metadata_validation_status='Y', source_metadata_key=self.key_value, source_metadata_validation_date=timezone.now(), source_metadata_extraction_date=timezone.now()) metadata_ledger.save() test_data_dict = MetadataLedger.objects.values( 'source_metadata').filter( source_metadata_validation_status='Y', record_lifecycle_status='Active').exclude( source_metadata_validation_date=None) transform_source_using_key(test_data_dict, self.source_target_mapping, self.test_required_column_names, self.expected_datatype) result_data = MetadataLedger.objects.filter( source_metadata_key=self.key_value, record_lifecycle_status='Active', source_metadata_validation_status='Y' ).values( 'source_metadata_transformation_date', 'target_metadata_key', 'target_metadata_key_hash', 'target_metadata', 'target_metadata_hash').first() result_data_supplemental = SupplementalLedger.objects.filter( supplemental_metadata_key=self.key_value, record_lifecycle_status='Active', ).values( 'supplemental_metadata_transformation_date', 'supplemental_metadata_key', 'supplemental_metadata_key_hash', 'supplemental_metadata', 'supplemental_metadata_hash').first() self.assertTrue(result_data.get('source_metadata_transformation_date')) self.assertTrue(result_data.get('target_metadata_key')) self.assertTrue(result_data.get('target_metadata_key_hash')) self.assertTrue(result_data.get('target_metadata')) self.assertTrue(result_data.get('target_metadata_hash')) self.assertTrue(result_data_supplemental. get('supplemental_metadata_transformation_date')) self.assertTrue(result_data_supplemental. get('supplemental_metadata_key')) self.assertTrue(result_data_supplemental. get('supplemental_metadata_key_hash')) self.assertTrue(result_data_supplemental. get('supplemental_metadata')) self.assertTrue(result_data_supplemental. get('supplemental_metadata_hash')) def test_store_transformed_source_metadata(self): """Test to store transformed metadata and supplemental metadata in metadata ledger """ metadata_ledger = MetadataLedger( source_metadata=self.source_metadata, source_metadata_key_hash=self.key_value_hash, source_metadata_validation_status='Y', record_lifecycle_status='Active', source_metadata_extraction_date=timezone.now() ) metadata_ledger.save() store_transformed_source_metadata(self.key_value, self.key_value_hash, self.target_metadata, self.hash_value, self.supplemental_data ) result_query = MetadataLedger.objects.values( 'source_metadata_transformation_date', 'target_metadata_key_hash', 'target_metadata', 'target_metadata_hash').filter( target_metadata_key_hash=self.key_value_hash).first() result_query_supplemental = SupplementalLedger.objects.values( 'supplemental_metadata_key_hash', 'supplemental_metadata_transformation_date', 'supplemental_metadata').filter( supplemental_metadata_key_hash=self.key_value_hash).first() self.assertTrue(result_query_supplemental. get('supplemental_metadata_transformation_date')) self.assertEqual(self.key_value_hash, result_query_supplemental.get( 'supplemental_metadata_key_hash')) self.assertEqual(self.supplemental_data, result_query_supplemental.get( 'supplemental_metadata')) self.assertTrue(result_query. get('source_metadata_transformation_date')) self.assertEqual(self.key_value_hash, result_query.get( 'target_metadata_key_hash')) self.assertEqual(self.target_metadata, result_query.get( 'target_metadata')) self.assertEqual(self.hash_value, result_query.get( 'target_metadata_hash')) # Test cases for validate_target_metadata def test_get_target_validation_schema(self): """Test to retrieve source validation schema from XIA configuration """ with patch('openlxp_xia.models.XIAConfiguration.field_overwrite'): xiaConfig = XIAConfiguration( target_metadata_schema='p2881_target_validation_schema.json') xiaConfig.save() result_dict = get_target_validation_schema() expected_dict = \ read_json_data('p2881_target_validation_schema.json') self.assertEqual(expected_dict, result_dict) def test_validate_target_using_key(self): """Test for Validating target data for required columns """ metadata_ledger = MetadataLedger( record_lifecycle_status='Active', source_metadata=self.source_metadata, target_metadata=self.target_metadata, target_metadata_hash=self.target_hash_value, target_metadata_key_hash=self.target_key_value_hash, target_metadata_key=self.target_key_value, source_metadata_transformation_date=timezone.now()) metadata_ledger.save() metadata_ledger_invalid = MetadataLedger( record_lifecycle_status='Active', source_metadata=self.metadata_invalid, target_metadata=self.target_metadata_invalid, target_metadata_hash=self.target_hash_value_invalid, target_metadata_key_hash=self.target_key_value_hash_invalid, target_metadata_key=self.target_key_value_invalid, source_metadata_transformation_date=timezone.now()) metadata_ledger_invalid.save() test_data = MetadataLedger.objects.values('target_metadata_key_hash', 'target_metadata').filter( target_metadata_validation_status='', record_lifecycle_status='Active' ).exclude( source_metadata_transformation_date=None) validate_target_using_key( test_data, self.test_target_required_column_names, self.recommended_column_name, self.expected_datatype) result_query = MetadataLedger.objects.values( 'target_metadata_validation_status', 'record_lifecycle_status'). \ filter(target_metadata_key_hash=self.target_key_value_hash).first() result_query_invalid = MetadataLedger.objects.values( 'target_metadata_validation_status', 'record_lifecycle_status'). \ filter(target_metadata_key_hash=self. target_key_value_hash_invalid).first() self.assertEqual('Y', result_query.get( 'target_metadata_validation_status')) self.assertEqual('Active', result_query.get( 'record_lifecycle_status')) self.assertEqual('N', result_query_invalid.get( 'target_metadata_validation_status')) # self.assertEqual('Inactive', result_query_invalid.get( # 'record_lifecycle_status')) def test_store_target_metadata_validation_status_valid(self): """Test to store validation status for valid target metadata in metadata ledger """ metadata_ledger = MetadataLedger( source_metadata=self.source_metadata, target_metadata=self.target_metadata, target_metadata_key_hash=self.key_value_hash) metadata_ledger.save() supplemental_ledger = SupplementalLedger( supplemental_metadata={"key": "value"}, supplemental_metadata_key_hash=self.key_value_hash) supplemental_ledger.save() store_target_metadata_validation_status(MetadataLedger.objects. values('target_metadata'), self.key_value_hash, 'Y', 'Active', MetadataLedger. objects. values('target_metadata') ) result_query = MetadataLedger.objects.values( 'target_metadata_validation_status', 'target_metadata_validation_date', 'record_lifecycle_status').filter( target_metadata_key_hash=self.key_value_hash).first() result_query_supplemental = SupplementalLedger.objects.values( 'supplemental_metadata_validation_date').filter( supplemental_metadata_key_hash=self.key_value_hash).first() self.assertTrue(result_query_supplemental. get('supplemental_metadata_validation_date')) self.assertEqual("Y", result_query.get( 'target_metadata_validation_status')) self.assertEqual('Active', result_query.get( 'record_lifecycle_status')) def test_store_target_metadata_validation_status_invalid(self): """Test to store validation status for invalid target metadata in metadata ledger """ metadata_ledger = MetadataLedger( source_metadata=self.source_metadata, target_metadata=self.target_metadata, target_metadata_key_hash=self.key_value_hash) metadata_ledger.save() supplemental_ledger = SupplementalLedger( supplemental_metadata={"key": "value"}, supplemental_metadata_key_hash=self.key_value_hash) supplemental_ledger.save() store_target_metadata_validation_status(MetadataLedger.objects. values('target_metadata'), self.key_value_hash, 'N', 'Inactive', MetadataLedger.objects. values('target_metadata') ) result_query = MetadataLedger.objects.values( 'metadata_record_inactivation_date', 'target_metadata_validation_status', 'target_metadata_validation_date', 'record_lifecycle_status').filter( target_metadata_key_hash=self.key_value_hash).first() result_query_supplemental = SupplementalLedger.objects.values( 'supplemental_metadata_validation_date').filter( supplemental_metadata_key_hash=self.key_value_hash).first() self.assertTrue(result_query_supplemental. get('supplemental_metadata_validation_date')) self.assertTrue(result_query.get('target_metadata_validation_date')) self.assertTrue(result_query.get('metadata_record_inactivation_date')) self.assertEqual("N", result_query.get( 'target_metadata_validation_status')) self.assertEqual('Inactive', result_query.get( 'record_lifecycle_status')) # Test cases for load_target_metadata def test_rename_metadata_ledger_fields(self): """Test for Renaming XIA column names to match with XIS column names""" with patch('openlxp_xia.models.XIAConfiguration.field_overwrite'): xiaConfig = XIAConfiguration(publisher='AGENT') xiaConfig.save() return_data = rename_metadata_ledger_fields(self.xia_data) self.assertEquals(self.xis_expected_data['metadata_hash'], return_data['metadata_hash']) self.assertEquals(self.xis_expected_data['metadata_key'], return_data['metadata_key']) self.assertEquals(self.xis_expected_data['metadata_key_hash'], return_data['metadata_key_hash']) self.assertEquals(self.xis_expected_data['provider_name'], return_data['provider_name']) def test_post_data_to_xis_response_201(self): """POSTing XIA metadata_ledger to XIS metadata_ledger and receive response status code 201""" with patch('openlxp_xia.models.XIAConfiguration.field_overwrite'): metadata_ledger = MetadataLedger( record_lifecycle_status='Active', source_metadata=self.source_metadata, target_metadata=self.target_metadata, target_metadata_hash=self.target_hash_value, target_metadata_key_hash=self.target_key_value_hash, target_metadata_key=self.target_key_value, source_metadata_transformation_date=timezone.now(), target_metadata_validation_status='Y', source_metadata_validation_status='Y', target_metadata_transmission_status='Ready') metadata_ledger.save() input_data = MetadataLedger.objects.filter( record_lifecycle_status='Active', target_metadata_validation_status='Y', target_metadata_transmission_status='Ready').values( 'metadata_record_uuid', 'target_metadata', 'target_metadata_hash', 'target_metadata_key', 'target_metadata_key_hash') xiaConfig = XIAConfiguration(publisher='AGENT') xiaConfig.save() xisConfig = XISConfiguration( xis_metadata_api_endpoint=self.xis_api_endpoint_url) xisConfig.save() with patch('requests.post') as response_obj: response_obj.return_value = response_obj response_obj.status_code = 201 post_data_to_xis(input_data) result_query = MetadataLedger.objects.values( 'target_metadata_transmission_status_code', 'target_metadata_transmission_status').filter( target_metadata_key=self.target_key_value).first() self.assertEqual(201, result_query.get( 'target_metadata_transmission_status_code')) self.assertEqual('Successful', result_query.get( 'target_metadata_transmission_status')) def test_post_data_to_xis_responses_other_than_201(self): """POSTing XIA metadata_ledger to XIS metadata_ledger and receive response status code 201""" with patch('openlxp_xia.models.XIAConfiguration.field_overwrite'): metadata_ledger = MetadataLedger( record_lifecycle_status='Active', source_metadata=self.source_metadata, target_metadata=self.target_metadata, target_metadata_hash=self.target_hash_value, target_metadata_key_hash=self.target_key_value_hash, target_metadata_key=self.target_key_value, source_metadata_transformation_date=timezone.now(), target_metadata_validation_status='Y', source_metadata_validation_status='Y', target_metadata_transmission_status='Ready') metadata_ledger.save() input_data = MetadataLedger.objects.filter( record_lifecycle_status='Active', target_metadata_validation_status='Y', target_metadata_transmission_status='Ready').values( 'metadata_record_uuid', 'target_metadata', 'target_metadata_hash', 'target_metadata_key', 'target_metadata_key_hash') xiaConfig = XIAConfiguration(publisher='AGENT') xiaConfig.save() xisConfig = XISConfiguration( xis_metadata_api_endpoint=self.xis_api_endpoint_url) xisConfig.save() with patch('requests.post') as response_obj: response_obj.return_value = response_obj response_obj.status_code = 400 post_data_to_xis(input_data) result_query = MetadataLedger.objects.values( 'target_metadata_transmission_status_code', 'target_metadata_transmission_status').filter( target_metadata_key=self.target_key_value).first() self.assertEqual(400, result_query.get( 'target_metadata_transmission_status_code')) self.assertEqual('Failed', result_query.get( 'target_metadata_transmission_status'))

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null

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7

4752801fb7c78daddf83018117e0730dbe421be7

172

py

Python

apps/main/views.py

sparcs-kaist/araplus

031ce946b393c5035dbfbb3e7233cc5dae61f440

[ "MIT" ]

17

2015-06-30T09:03:37.000Z

2016-01-26T16:54:01.000Z

apps/main/views.py

sparcs-kaist/araplus

031ce946b393c5035dbfbb3e7233cc5dae61f440

[ "MIT" ]

136

2015-07-01T18:49:51.000Z

2016-07-19T14:58:31.000Z

apps/main/views.py

sparcs-kaist/araplus

031ce946b393c5035dbfbb3e7233cc5dae61f440

[ "MIT" ]

11

2015-07-01T18:36:06.000Z

2018-12-19T02:52:09.000Z

from django.shortcuts import render def home(request): return render(request, 'main/main.html') def credit(request): return render(request, 'main/credit.html')

17.2

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0.726744

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5.434783

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1

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8

475c31f20024704f71ea8dd7f1c8f3e000b2636e

8,300

py

Python

tests_scripts/Sprint5/HiddenDefaultFilters.py

vineethreddyramasa/uno-community-partnership

694886b7ad7fa98f6dbb24b03476962cfadebc70

[ "MIT" ]

13

2018-08-30T16:03:18.000Z

2019-11-25T07:08:43.000Z

tests_scripts/Sprint5/HiddenDefaultFilters.py

vineethreddyramasa/uno-community-partnership

694886b7ad7fa98f6dbb24b03476962cfadebc70

[ "MIT" ]

814

2018-08-30T02:28:55.000Z

2022-03-11T23:31:45.000Z

tests_scripts/Sprint5/HiddenDefaultFilters.py

vineethreddyramasa/uno-community-partnership

694886b7ad7fa98f6dbb24b03476962cfadebc70

[ "MIT" ]

6

2018-09-16T05:35:49.000Z

2019-10-17T02:44:19.000Z

from tests_scripts import * import unittest from selenium import webdriver from selenium.webdriver.common.keys import Keys from selenium.webdriver.support.ui import Select import os class HiddenDefaultFilters(unittest.TestCase): def setUp(self): pathname = os.path.join(os.getcwd(), "chromedriver") self.driver = webdriver.Chrome(pathname) def test_hidden_filters_not_logged_in(self): driver = self.driver # self.email = community_partner_user # self.password = community_partner_pwd driver.maximize_window() # REPORTS driver.get(sta_url + 'projectInfo/') self.assertFalse(driver.find_element_by_id('id_academic_year').is_displayed()) driver.get(sta_url + 'engageType/') self.assertFalse(driver.find_element_by_id('id_academic_year').is_displayed()) driver.get(sta_url + 'communitypublicreport/') self.assertFalse(driver.find_element_by_id('id_academic_year').is_displayed()) driver.get(sta_url + 'projectspublicreport/') self.assertFalse(driver.find_element_by_id('id_academic_year').is_displayed()) # CHARTS driver.get(sta_url + 'missionchart/') self.assertFalse(driver.find_element_by_id('id_academicyear').is_displayed()) driver.get(sta_url + 'engagementtypechart2/') self.assertFalse(driver.find_element_by_id('id_academic_year').is_displayed()) # def test_filters_remain_opened_when_selected_not_logged_in(self): # driver = self.driver # # self.email = community_partner_user # # self.password = community_partner_pwd # # driver.maximize_window() # # # REPORTS # driver.get(sta_url + 'projectInfo/') # driver.find_element_by_xpath("//INPUT[@id='btn']/preceding-sibling::INPUT").click() # select = Select(driver.find_element_by_id('id_academic_year')) # select.select_by_index(2) # self.assertTrue(driver.find_element_by_id('id_academic_year').is_displayed()) # # driver.get(sta_url + 'engageType/') # driver.find_element_by_xpath("//INPUT[@id='btn']/preceding-sibling::INPUT").click() # select = Select(driver.find_element_by_id('id_academic_year')) # select.select_by_index(2) # self.assertTrue(driver.find_element_by_id('id_academic_year').is_displayed()) # # driver.get(sta_url + 'communitypublicreport/') # driver.find_element_by_xpath("//INPUT[@id='btn']/preceding-sibling::INPUT").click() # select = Select(driver.find_element_by_id('id_academic_year')) # select.select_by_index(2) # self.assertTrue(driver.find_element_by_id('id_academic_year').is_displayed()) # # driver.get(sta_url + 'projectspublicreport/') # driver.find_element_by_xpath("//INPUT[@id='btn']/preceding-sibling::INPUT").click() # select = Select(driver.find_element_by_id('id_academic_year')) # select.select_by_index(2) # self.assertTrue(driver.find_element_by_id('id_academic_year').is_displayed()) # # # CHARTS # driver.get(sta_url + 'missionchart/') # driver.find_element_by_xpath("//INPUT[@id='btn']/preceding-sibling::INPUT").click() # select = Select(driver.find_element_by_id('id_academicyear')) # select.select_by_index(2) # self.assertTrue(driver.find_element_by_id('id_academicyear').is_displayed()) # # driver.get(sta_url + 'engagementtypechart2/') # driver.find_element_by_xpath("//INPUT[@id='btn']/preceding-sibling::INPUT").click() # select = Select(driver.find_element_by_id('id_academic_year')) # select.select_by_index(2) # self.assertTrue(driver.find_element_by_id('id_academic_year').is_displayed()) def test_hidden_filters_logged_in(self): driver = self.driver self.email = community_partner_user self.password = community_partner_pwd driver.get(sta_url) driver.find_element_by_link_text("Login").click() driver.find_element_by_name("email").click() driver.find_element_by_name("email").clear() driver.find_element_by_name("email").send_keys(self.email) driver.find_element_by_name("password").clear() driver.find_element_by_name("password").send_keys(self.password) driver.find_element_by_name("password").send_keys(Keys.ENTER) driver.maximize_window() # REPORTS driver.get(sta_url + 'projectInfo/') self.assertFalse(driver.find_element_by_id('id_academic_year').is_displayed()) driver.get(sta_url + 'engageType/') self.assertFalse(driver.find_element_by_id('id_academic_year').is_displayed()) driver.get(sta_url + 'communitypublicreport/') self.assertFalse(driver.find_element_by_id('id_academic_year').is_displayed()) driver.get(sta_url + 'projectspublicreport/') self.assertFalse(driver.find_element_by_id('id_academic_year').is_displayed()) # CHARTS driver.get(sta_url + 'missionchart/') self.assertFalse(driver.find_element_by_id('id_academicyear').is_displayed()) driver.get(sta_url + 'engagementtypechart2/') self.assertFalse(driver.find_element_by_id('id_academic_year').is_displayed()) # def test_filters_remain_opened_when_selected_logged_in(self): # driver = self.driver # self.email = community_partner_user # self.password = community_partner_pwd # # driver.get(sta_url) # driver.find_element_by_link_text("Login").click() # driver.find_element_by_name("email").click() # driver.find_element_by_name("email").clear() # driver.find_element_by_name("email").send_keys(self.email) # driver.find_element_by_name("password").clear() # driver.find_element_by_name("password").send_keys(self.password) # driver.find_element_by_name("password").send_keys(Keys.ENTER) # # driver.maximize_window() # # # REPORTS # driver.get(sta_url + 'projectInfo/') # driver.find_element_by_xpath("//INPUT[@id='btn']/preceding-sibling::INPUT").click() # select = Select(driver.find_element_by_id('id_academic_year')) # select.select_by_index(2) # self.assertTrue(driver.find_element_by_id('id_academic_year').is_displayed()) # # driver.get(sta_url + 'engageType/') # driver.find_element_by_xpath("//INPUT[@id='btn']/preceding-sibling::INPUT").click() # select = Select(driver.find_element_by_id('id_academic_year')) # select.select_by_index(2) # self.assertTrue(driver.find_element_by_id('id_academic_year').is_displayed()) # # driver.get(sta_url + 'communitypublicreport/') # driver.find_element_by_xpath("//INPUT[@id='btn']/preceding-sibling::INPUT").click() # select = Select(driver.find_element_by_id('id_academic_year')) # select.select_by_index(2) # self.assertTrue(driver.find_element_by_id('id_academic_year').is_displayed()) # # driver.get(sta_url + 'projectspublicreport/') # driver.find_element_by_xpath("//INPUT[@id='btn']/preceding-sibling::INPUT").click() # select = Select(driver.find_element_by_id('id_academic_year')) # select.select_by_index(2) # self.assertTrue(driver.find_element_by_id('id_academic_year').is_displayed()) # # # CHARTS # driver.get(sta_url + 'missionchart/') # driver.find_element_by_xpath("//INPUT[@id='btn']/preceding-sibling::INPUT").click() # select = Select(driver.find_element_by_id('id_academicyear')) # select.select_by_index(2) # self.assertTrue(driver.find_element_by_id('id_academicyear').is_displayed()) # # driver.get(sta_url + 'engagementtypechart2/') # driver.find_element_by_xpath("//INPUT[@id='btn']/preceding-sibling::INPUT").click() # select = Select(driver.find_element_by_id('id_academic_year')) # select.select_by_index(2) # self.assertTrue(driver.find_element_by_id('id_academic_year').is_displayed()) def tearDown(self): self.driver.close() self.driver.stop_client() if __name__ == "__main__": unittest.main()

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9

479cb88083385a94e7b7540374db837a62d87749

20,884

py

Python

ssb_sparktools/editing/editing.py

statisticsnorway/SSB_Spark_tools

95271519b0babcfbc9ec2c93503e287d776eaedb

[ "Apache-2.0" ]

1

2021-06-25T06:16:50.000Z

ssb_sparktools/editing/editing.py

statisticsnorway/SSB_Spark_tools

95271519b0babcfbc9ec2c93503e287d776eaedb

[ "Apache-2.0" ]

6

2020-09-04T07:32:29.000Z

2021-07-08T11:04:02.000Z

ssb_sparktools/editing/editing.py

statisticsnorway/SSB_Spark_tools

95271519b0babcfbc9ec2c93503e287d776eaedb

[ "Apache-2.0" ]

null

from pyspark import Row from pyspark.sql import SparkSession from pyspark.sql import SQLContext from pyspark.sql.types import * from pyspark.sql import DataFrame from itertools import chain import pyspark.sql.functions as F from pyspark import SparkContext import pandas as pd from collections import OrderedDict import numbers from pyspark.sql import DataFrame def listcode_lookup(df, luvar, kodeliste, nokkelverdi, spark_session=None): ''' This function adds a new variable to a given dataframe. The added variable contains values that correspond to the values in a variable in the original dataset. For example; if the variable on the original dataset is the municipality code, then the function can add the name of the municipality corresponding to the municipality code. :param df: The dataframe containing the variable of interest :param luvar: the name of the variable of interest in the supplied dataframe :param kodeliste: the list of codes to use for lookup :param nokkelverdi: Python list ([key value, lookup value]). Key value is the name of the variable in the list of codes which corresponds to the variable of interest in the dataframe. Lookup value is the name of the variable in the list of codes to be returned and added to the dataframe. :param spark_session: defines the Spark session to be used by the function. Default is None, which means the function tries to catch the current session. :type df: Spark dataframe :type luvar: string :type kodeliste: dataframe :type nokkelverdi: list :type spark_session: string Returns: Dataframe: Spark dataframe consisting of the original dataframe updated with a new variable containing the lookup values corresponding to the values of the variable luvar. ''' #Sjekker om parametre er av korrekt format if (isinstance(df, DataFrame)) & (isinstance(luvar, str)) & (isinstance(kodeliste, DataFrame)) & (isinstance(nokkelverdi, type([]))): #Inititerer variabler if spark_session is None: spark = SparkSession.builder.getOrCreate() else: spark = spark_session kodeliste_dict = {} #Henter nøkkelvariabel og oppslagsvariabel og lager en dictionary av det for row in kodeliste.rdd.collect(): kodeliste_dict[row[nokkelverdi[0]]] = row[nokkelverdi[1]] #Gjør oppslag mot dictionary på variabel vi ønsker og oppretter en egen variabel for resultatet av oppslaget mapping_expr = F.create_map([F.lit(x) for x in chain(*kodeliste_dict.items())]) df = df.withColumn(nokkelverdi[1].format(luvar), mapping_expr.getItem(F.col(luvar))) #Returnere datasettet med ny variabel som resultat av oppslag return df else: #Hvis ikke parametre sendt med funksjonen er korrekt format skrives det ut en feilmelding if not (isinstance(df, DataFrame)): raise Exception('Første parameter må være en dataframe som har variabelen som skal brukes til å slå opp i kodeliste') return if not (isinstance(luvar, str)): raise Exception('Andre parameter må være en string med navnet på variabel som skal brukes til å slå opp i kodeliste') return if not (isinstance(kodeliste, DataFrame)): raise Exception('Tredje parameter må være en dataframe som inneholder kodelisten variabel skal slå opp i') return if not (isinstance(kodeliste, type([]))): raise Exception('Fjerde parameter må være en python liste der første verdi er nøkkelvariabel i kodeliste som variabelen\ sammenlignes med og den andre oppslagsvariabel som inneholder verdiene vi ønsker å få med på egen variabel tilbake') return def missing_correction_bool(df, correction_value=False, exception_for=[], df_name='', spark_session=None): ''' This function checks a dataframe for missing values on Boolean variables and replaces missing values with the correction_value parameter. Correction_value defaults to False if no value is given. The function corrects all Boolean variables except those specified in the exception_for parameter. All changes are logged and returned. :param df: The dataframe to be corrected :param correction_value: value to replace missing :param exception_for: list of variables not to be corrected :param spark_session: defines the Spark session to be used by the function. Default is None, which means the function tries to catch the current session. :type df: Spark dataframe :type correction_value: Boolean :type exception_for: list :type spark_session: string Returns: corrected dataframe and log in that order Dataframe: corrected dataframe (Spark) Dataframe: dataframe (Pandas) with log of number of corrections per variable ''' if (isinstance(df, DataFrame)) & (isinstance(correction_value, bool)) & (isinstance(exception_for, type([]))): #initialiserer variabler if spark_session is None: spark = SparkSession.builder.getOrCreate() else: spark = spark_session boollist = [] #Legger alle boolske variabler i en egen liste for k in df.schema.fields: if k.name not in exception_for: if (str(k.dataType) == 'BooleanType'): boollist.append(k.name) #Transformerer spark dataframe til pandas dataframe for å lage logg med opptellinger av korrigerte verdier df_count = df[boollist].toPandas() df_count = df_count.isnull().sum() df_count = df_count.to_dict(OrderedDict) df_log = [] if len(df_name)>0: corrected_missing_log = pd.DataFrame(columns=['dataframe', 'datatype', 'variabel', 'korrigeringer']) for k, v in df_count.items(): if v != 0: df_dict_count= {} df_dict_count['dataframe'] = df_name df_dict_count['variabel'] = k df_dict_count['datatype'] = 'boolean' df_dict_count['korrigeringer'] = v df_log.append(df_dict_count) else: corrected_missing_log = pd.DataFrame(columns=['datatype', 'variabel', 'korrigeringer']) for k, v in df_count.items(): if v != 0: df_dict_count= {} df_dict_count['variabel'] = k df_dict_count['datatype'] = 'boolean' df_dict_count['korrigeringer'] = v df_log.append(df_dict_count) df_log_df = pd.DataFrame(df_log) #Korrigerer verdier som er boolske df = df.fillna(correction_value, subset=boollist) #Returnerer korrigert dataframe (spark) og dictionary med log over antall korrigeringer per variabel return df, df_log_df else: if not (isinstance(df, DataFrame)): raise Exception('Parameter df må være en dataframe') return if not (isinstance(correction_value, numbers.Number)): raise Exception('Parameter correction_value må være boolsk format') return if not (isinstance(exception_for, type([]))): raise Exception('Parameter exception_for må være liste format') return def missing_correction_number(df, correction_value=0, exception_for=[], df_name='', spark_session=None): ''' This function checks a dataframe for missing values on numeric variables and replaces missing values with the correction_value parameter. Correction_value defaults to zero if no value is given. The function corrects all numeric variables except those specified in the exception_for parameter. All changes are logged and returned. :param df: The dataframe to be corrected :param correction_value: value to replace missing :param exception_for: list of variables not to be corrected :param spark_session: defines the Spark session to be used by the function. Default is None, which means the function tries to catch the current session. :type df: Spark dataframe :type correction_value: numeric :type exception_for: list :type spark_session: string Returns: corrected dataframe and log in that order Dataframe: corrected dataframe (Spark) Dataframe: dataframe (Pandas) with log of number of corrections per variable ''' if (isinstance(df, DataFrame)) & (isinstance(correction_value, numbers.Number)) & (isinstance(exception_for, type([]))): #initialiserer variabler if spark_session is None: spark = SparkSession.builder.getOrCreate() else: spark = spark_session numlist = [] #Legger alle numeriske variabler i en egen liste for k in df.schema.fields: if k.name not in exception_for: if str(k.dataType) in ['LongType', 'ByteType', 'ShortType', 'IntegerType', 'FloatType', 'DoubleType', 'DecimalType']: numlist.append(k.name) #Transformerer spark dataframe til pandas dataframe for å lage logg med opptellinger av korrigerte verdier df_count = df[numlist].toPandas() df_count = df_count.isnull().sum() df_count = df_count.to_dict(OrderedDict) df_log = [] if len(df_name)>0: corrected_missing_log = pd.DataFrame(columns=['dataframe', 'datatype', 'variable', 'corrections']) for k, v in df_count.items(): if v != 0: df_dict_count= {} df_dict_count['dataframe'] = df_name df_dict_count['variable'] = k df_dict_count['datatype'] = 'numeric' df_dict_count['corrections'] = v df_log.append(df_dict_count) else: corrected_missing_log = pd.DataFrame(columns=['datatype', 'variable', 'corrections']) for k, v in df_count.items(): if v != 0: df_dict_count= {} df_dict_count['variable'] = k df_dict_count['datatype'] = 'numeric' df_dict_count['corrections'] = v df_log.append(df_dict_count) df_log_df = pd.DataFrame(df_log) #Korrigerer verdier som er numeriske df = df.fillna(correction_value, subset=numlist) #Returnerer korrigert dataframe (spark) og dictionary med log over antall korrigeringer per variabel return df, df_log_df else: if not (isinstance(df, DataFrame)): raise Exception('Parameter df må være en dataframe') return if not (isinstance(correction_value, numbers.Number)): raise Exception('Parameter correction_value må være numerisk format') return if not (isinstance(exception_for, type([]))): raise Exception('Parameter exception_for må være liste format') return def spark_missing_correction_bool(df, correction_value=False, exception_for=[], df_name='', spark_session=None): #Parameter df --> datasett som det skal kjøres opptelling av missing for #Paramater correction_value --> hvilken verdi som skal settes inn istedenfor missing #Parameter exception_for --> liste over variable som ikke skal korrigeres ''' This function checks a dataframe for missing values on Boolean variables and replaces missing values with the correction_value parameter. Correction_value defaults to False if no value is given. The function corrects all Boolean variables except those specified in the exception_for parameter. All changes are logged and returned. :param df: The dataframe to be corrected :param correction_value: value to replace missing :param exception_for: list of variables not to be corrected :param spark_session: defines the Spark session to be used by the function. Default is None, which means the function tries to catch the current session. :type df: Spark dataframe :type correction_value: Boolean :type exception_for: list :type spark_session: string Returns: corrected dataframe and log in that order Dataframe: corrected dataframe (Spark) Dataframe: dataframe (Spark) with log of number of corrections per variable ''' if (isinstance(df, DataFrame)) & (isinstance(correction_value, bool)) & (isinstance(exception_for, type([]))): #initialiserer variabler if spark_session is None: spark = SparkSession.builder.getOrCreate() else: spark = spark_session boollist = [] #Legger alle boolske variabler i en egen liste for k in df.schema.fields: if k.name not in exception_for: if (str(k.dataType) == 'BooleanType'): boollist.append(k.name) #Lager en logg df_count = df[boollist].select([F.count(F.when(F.isnull(c), c)).alias(c) for c in df[boollist].columns]) df_columns = df_count.columns df_log = [] if len(df_name)>0: missing_variabler = [StructField('dataframe', StringType(), False),\ StructField('variable', StringType(), True),\ StructField('datatype', StringType(), True),\ StructField('corrections', IntegerType(), False)] missing_schema = StructType(missing_variabler) for row in df_count.rdd.collect(): for k in df_columns: if row[k]!=0: df_dict_count= {} df_dict_count['dataframe'] = df_name df_dict_count['variable'] = k df_dict_count['datatype'] = 'boolean' df_dict_count['corrections'] = row[k] df_log.append(df_dict_count) else: missing_variabler = [StructField('variable', StringType(), True),\ StructField('datatype', StringType(), True),\ StructField('corrections', IntegerType(), False)] missing_schema = StructType(missing_variabler) for row in df_count.rdd.collect(): for k in df_columns: if row[k]!=0: df_dict_count= {} df_dict_count['variable'] = k df_dict_count['datatype'] = 'boolean' df_dict_count['corrections'] = row[k] df_log.append(df_dict_count) if len(df_log)>0: rdd_missing = spark.sparkContext.parallelize(df_log) df_corrections = spark.createDataFrame(rdd_missing, missing_schema) else: df_corrections = spark.createDataFrame(spark.sparkContext.emptyRDD(), missing_schema) #Korrigerer verdier som er boolske df = df.fillna(correction_value, subset=boollist) #Returnerer korrigert dataframe (spark) og dictionary med log over antall korrigeringer per variabel return df, df_corrections else: if not (isinstance(df, DataFrame)): raise Exception('Parameter df må være en dataframe') return if not (isinstance(correction_value, numbers.Number)): raise Exception('Parameter correction_value må være boolsk format') return if not (isinstance(exception_for, type([]))): raise Exception('Parameter exception_for må være liste format') return def spark_missing_correction_number(df, correction_value=0, exception_for=[], df_name='', spark_session=None): ''' This function checks a dataframe for missing values on numeric variables and replaces missing values with the correction_value parameter. Correction_value defaults to zero if no value is given. The function corrects all numeric variables except those specified in the exception_for parameter. All changes are logged and returned. :param df: The dataframe to be corrected :param correction_value: value to replace missing :param exception_for: list of variables not to be corrected :param spark_session: defines the Spark session to be used by the function. Default is None, which means the function tries to catch the current session. :type df: Spark dataframe :type correction_value: numeric :type exception_for: list :type spark_session: string Returns: corrected dataframe and log in that order Dataframe: corrected dataframe (Spark) Dataframe: dataframe (Spark) with log of number of corrections per variable ''' if (isinstance(df, DataFrame)) & (isinstance(correction_value, numbers.Number)) & (isinstance(exception_for, type([]))): #initialiserer variabler if spark_session is None: spark = SparkSession.builder.getOrCreate() else: spark = spark_session numlist = [] #Legger alle numeriske variabler i en egen liste for k in df.schema.fields: if k.name not in exception_for: if str(k.dataType) in ['LongType', 'ByteType', 'ShortType', 'IntegerType', 'FloatType', 'DoubleType', 'DecimalType']: numlist.append(k.name) df_count = df[numlist].select([F.count(F.when(F.isnull(c), c)).alias(c) for c in df[numlist].columns]) df_columns = df_count.columns df_log = [] if len(df_name)>0: missing_variabler = [StructField('dataframe', StringType(), False),\ StructField('variable', StringType(), True),\ StructField('datatype', StringType(), True),\ StructField('corrections', IntegerType(), False)] missing_schema = StructType(missing_variabler) for row in df_count.rdd.collect(): for k in df_columns: if row[k]!=0: df_dict_count= {} df_dict_count['dataframe'] = df_name df_dict_count['variable'] = k df_dict_count['datatype'] = 'numeric' df_dict_count['corrections'] = row[k] df_log.append(df_dict_count) else: missing_variabler = [StructField('variabel', StringType(), True),\ StructField('datatype', StringType(), True),\ StructField('corrections', IntegerType(), False)] missing_schema = StructType(missing_variabler) for row in df_count.rdd.collect(): for k in df_columns: if row[k]!=0: df_dict_count= {} df_dict_count['variable'] = k df_dict_count['datatype'] = 'numeric' df_dict_count['corrections'] = row[k] df_log.append(df_dict_count) if len(df_log)>0: rdd_missing = spark.sparkContext.parallelize(df_log) df_corrections = spark.createDataFrame(rdd_missing, missing_schema) else: df_corrections = spark.createDataFrame(spark.sparkContext.emptyRDD(), missing_schema) #Korrigerer verdier som er numeriske df = df.fillna(correction_value, subset=numlist) #Returnerer korrigert dataframe (spark) og dictionary med log over antall korrigeringer per variabel return df, df_corrections else: if not (isinstance(df, DataFrame)): raise Exception('Parameter df må være en dataframe') return if not (isinstance(correction_value, numbers.Number)): raise Exception('Parameter correction_value må være numerisk format') return if not (isinstance(exception_for, type([]))): raise Exception('Parameter exception_for må være liste format') return

46.101545

148

0.617841

2,401

20,884

5.24823

0.11287

0.020951

0.03841

0.018332

0.825569

0.810888

0.79954

0.796365

0

0.001315

0.30837

20,884

452

149

46.20354

0.871088

0.325943

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0.111226

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false

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0

null

0

1

0

1

0

null

0

7

47dc15cbad600f98414ec1d3df3269bb306bfe01

67

py

Python

PicoCTF-2018/what_base_is_it/main.py

ThomasMiller01/CTF

6e4c76d84fe55326fe228e0375c7d39dd4160d4c

[ "MIT" ]

1

2019-12-18T13:49:34.000Z

PicoCTF-2018/what_base_is_it/main.py

ThomasMiller01/CTF

6e4c76d84fe55326fe228e0375c7d39dd4160d4c

[ "MIT" ]

null

PicoCTF-2018/what_base_is_it/main.py

ThomasMiller01/CTF

6e4c76d84fe55326fe228e0375c7d39dd4160d4c

[ "MIT" ]

null

print(str(int("01110000 01101000 01101111 01101110 01100101", 2)))

33.5

66

0.776119

9

67

5.777778

1

0

0.672131

0.089552

67

1

67

0.180328

0

0.656716

0

1

0

true

0

1

0

null

0

1

0

1

0

1

0

1

0

null

0

1

0

1

0

7

d018f43bb1642ffef194964fdd12baad16af4174

109,946

py

Python

pyclue/pb/clue_pb2.py

linewalks/py-clue

ecea2a37d88387d909fc283fdbc145bc5a1187a8

[ "MIT" ]

null

pyclue/pb/clue_pb2.py

linewalks/py-clue

ecea2a37d88387d909fc283fdbc145bc5a1187a8

[ "MIT" ]

11

2022-01-13T09:30:03.000Z

2022-03-14T01:10:08.000Z

pyclue/pb/clue_pb2.py

linewalks/py-clue

ecea2a37d88387d909fc283fdbc145bc5a1187a8

[ "MIT" ]

null

# -*- coding: utf-8 -*- # Generated by the protocol buffer compiler. DO NOT EDIT! # source: clue.proto """Generated protocol buffer code.""" from google.protobuf import descriptor as _descriptor from google.protobuf import message as _message from google.protobuf import reflection as _reflection from google.protobuf import symbol_database as _symbol_database # @@protoc_insertion_point(imports) _sym_db = _symbol_database.Default() DESCRIPTOR = _descriptor.FileDescriptor( name='clue.proto', package='', syntax='proto3', serialized_options=None, create_key=_descriptor._internal_create_key, serialized_pb=b'\n\nclue.proto\"/\n\x0cRequestLogin\x12\r\n\x05\x65mail\x18\x01 \x01(\t\x12\x10\n\x08password\x18\x02 \x01(\t\"<\n\rResponseLogin\x12\x14\n\x0c\x61\x63\x63\x65ss_token\x18\x01 \x01(\t\x12\x15\n\rrefresh_token\x18\x02 \x01(\t\"?\n\x11RequestCohortList\x12\x0c\n\x04term\x18\x01 \x01(\t\x12\x0c\n\x04page\x18\x02 \x01(\x05\x12\x0e\n\x06length\x18\x03 \x01(\x05\"\x86\x01\n\nCohortInfo\x12\n\n\x02id\x18\x01 \x01(\x05\x12\x0c\n\x04name\x18\x02 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) _REQUESTLOGIN = _descriptor.Descriptor( name='RequestLogin', full_name='RequestLogin', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='email', full_name='RequestLogin.email', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='password', full_name='RequestLogin.password', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=14, serialized_end=61, ) _RESPONSELOGIN = _descriptor.Descriptor( name='ResponseLogin', full_name='ResponseLogin', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='access_token', full_name='ResponseLogin.access_token', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='refresh_token', full_name='ResponseLogin.refresh_token', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=63, serialized_end=123, ) _REQUESTCOHORTLIST = _descriptor.Descriptor( name='RequestCohortList', full_name='RequestCohortList', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='term', full_name='RequestCohortList.term', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='page', full_name='RequestCohortList.page', index=1, number=2, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='length', full_name='RequestCohortList.length', index=2, number=3, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=125, serialized_end=188, ) _COHORTINFO = _descriptor.Descriptor( name='CohortInfo', full_name='CohortInfo', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='id', full_name='CohortInfo.id', index=0, number=1, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='name', full_name='CohortInfo.name', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='generated_time', full_name='CohortInfo.generated_time', index=2, number=3, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='person_count', full_name='CohortInfo.person_count', index=3, number=4, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='done', full_name='CohortInfo.done', index=4, number=5, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='update_flag', full_name='CohortInfo.update_flag', index=5, number=6, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='state', full_name='CohortInfo.state', index=6, number=7, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=191, serialized_end=325, ) _RESPONSECOHORTLIST = _descriptor.Descriptor( name='ResponseCohortList', full_name='ResponseCohortList', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='cohort_list', full_name='ResponseCohortList.cohort_list', index=0, number=1, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=327, serialized_end=381, ) _REQUESTCOHORTSTREAM = _descriptor.Descriptor( name='RequestCohortStream', full_name='RequestCohortStream', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='fetch_num', full_name='RequestCohortStream.fetch_num', index=0, number=1, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='cohort_id', full_name='RequestCohortStream.cohort_id', index=1, number=2, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=383, serialized_end=442, ) _PERSONINFO = _descriptor.Descriptor( name='PersonInfo', full_name='PersonInfo', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='person_id', full_name='PersonInfo.person_id', index=0, number=1, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='gender_concept_id', full_name='PersonInfo.gender_concept_id', index=1, number=2, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='year_of_birth', full_name='PersonInfo.year_of_birth', index=2, number=3, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='race_concept_id', full_name='PersonInfo.race_concept_id', index=3, number=4, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='ethnicity_concept_id', full_name='PersonInfo.ethnicity_concept_id', index=4, number=5, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='month_of_birth', full_name='PersonInfo.month_of_birth', index=5, number=6, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='day_of_birth', full_name='PersonInfo.day_of_birth', index=6, number=7, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='birth_datetime', full_name='PersonInfo.birth_datetime', index=7, number=8, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='location_id', full_name='PersonInfo.location_id', index=8, number=9, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='provider_id', full_name='PersonInfo.provider_id', index=9, number=10, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='care_site_id', full_name='PersonInfo.care_site_id', index=10, number=11, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='person_source_value', full_name='PersonInfo.person_source_value', index=11, number=12, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='gender_source_value', full_name='PersonInfo.gender_source_value', index=12, number=13, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='gender_source_concept_id', full_name='PersonInfo.gender_source_concept_id', index=13, number=14, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='race_source_value', full_name='PersonInfo.race_source_value', index=14, number=15, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='race_source_concept_id', full_name='PersonInfo.race_source_concept_id', index=15, number=16, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='ethnicity_source_value', full_name='PersonInfo.ethnicity_source_value', index=16, number=17, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='ethnicity_source_concept_id', full_name='PersonInfo.ethnicity_source_concept_id', index=17, number=18, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=445, serialized_end=935, ) _CONDITIONOCCURRENCEINFO = _descriptor.Descriptor( name='ConditionOccurrenceInfo', full_name='ConditionOccurrenceInfo', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='condition_occurrence_id', full_name='ConditionOccurrenceInfo.condition_occurrence_id', index=0, number=1, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='person_id', full_name='ConditionOccurrenceInfo.person_id', index=1, number=2, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='condition_concept_id', full_name='ConditionOccurrenceInfo.condition_concept_id', index=2, number=3, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='condition_start_date', full_name='ConditionOccurrenceInfo.condition_start_date', index=3, number=4, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='condition_type_concept_id', full_name='ConditionOccurrenceInfo.condition_type_concept_id', index=4, number=5, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='condition_start_datetime', full_name='ConditionOccurrenceInfo.condition_start_datetime', index=5, number=6, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='condition_end_date', full_name='ConditionOccurrenceInfo.condition_end_date', index=6, number=7, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='condition_end_datetime', full_name='ConditionOccurrenceInfo.condition_end_datetime', index=7, number=8, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='condition_status_concept_id', full_name='ConditionOccurrenceInfo.condition_status_concept_id', index=8, number=9, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='stop_reason', full_name='ConditionOccurrenceInfo.stop_reason', index=9, number=10, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='provider_id', full_name='ConditionOccurrenceInfo.provider_id', index=10, number=11, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='visit_occurrence_id', full_name='ConditionOccurrenceInfo.visit_occurrence_id', index=11, number=12, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='visit_detail_id', full_name='ConditionOccurrenceInfo.visit_detail_id', index=12, number=13, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='condition_source_value', full_name='ConditionOccurrenceInfo.condition_source_value', index=13, number=14, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='condition_source_concept_id', full_name='ConditionOccurrenceInfo.condition_source_concept_id', index=14, number=15, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='condition_status_source_value', full_name='ConditionOccurrenceInfo.condition_status_source_value', index=15, number=16, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=938, serialized_end=1445, ) _DEATHINFO = _descriptor.Descriptor( name='DeathInfo', full_name='DeathInfo', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='person_id', full_name='DeathInfo.person_id', index=0, number=1, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='death_date', full_name='DeathInfo.death_date', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='death_datetime', full_name='DeathInfo.death_datetime', index=2, number=3, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='death_type_concept_id', full_name='DeathInfo.death_type_concept_id', index=3, number=4, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='cause_concept_id', full_name='DeathInfo.cause_concept_id', index=4, number=5, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='cause_source_value', full_name='DeathInfo.cause_source_value', index=5, number=6, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='cause_source_concept_id', full_name='DeathInfo.cause_source_concept_id', index=6, number=7, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1448, serialized_end=1640, ) _DEVICEEXPOSUREINFO = _descriptor.Descriptor( name='DeviceExposureInfo', full_name='DeviceExposureInfo', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='device_exposure_id', full_name='DeviceExposureInfo.device_exposure_id', index=0, number=1, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='person_id', full_name='DeviceExposureInfo.person_id', index=1, number=2, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='device_concept_id', full_name='DeviceExposureInfo.device_concept_id', index=2, number=3, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='device_exposure_start_date', full_name='DeviceExposureInfo.device_exposure_start_date', index=3, number=4, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='device_type_concept_id', full_name='DeviceExposureInfo.device_type_concept_id', index=4, number=5, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='device_exposure_start_datetime', full_name='DeviceExposureInfo.device_exposure_start_datetime', index=5, number=6, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='device_exposure_end_date', full_name='DeviceExposureInfo.device_exposure_end_date', index=6, number=7, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='device_exposure_end_datetime', full_name='DeviceExposureInfo.device_exposure_end_datetime', index=7, number=8, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='unique_device_id', full_name='DeviceExposureInfo.unique_device_id', index=8, number=9, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='quantity', full_name='DeviceExposureInfo.quantity', index=9, number=10, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='provider_id', full_name='DeviceExposureInfo.provider_id', index=10, number=11, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='visit_occurrence_id', full_name='DeviceExposureInfo.visit_occurrence_id', index=11, number=12, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='visit_detail_id', full_name='DeviceExposureInfo.visit_detail_id', index=12, number=13, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='device_source_value', full_name='DeviceExposureInfo.device_source_value', index=13, number=14, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='device_source_concept_id', full_name='DeviceExposureInfo.device_source_concept_id', index=14, number=15, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1643, serialized_end=2099, ) _DRUGEXPOSUREINFO = _descriptor.Descriptor( name='DrugExposureInfo', full_name='DrugExposureInfo', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='drug_exposure_id', full_name='DrugExposureInfo.drug_exposure_id', index=0, number=1, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='person_id', full_name='DrugExposureInfo.person_id', index=1, number=2, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='drug_concept_id', full_name='DrugExposureInfo.drug_concept_id', index=2, number=3, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='drug_exposure_start_date', full_name='DrugExposureInfo.drug_exposure_start_date', index=3, number=4, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='drug_exposure_end_date', full_name='DrugExposureInfo.drug_exposure_end_date', index=4, number=5, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='drug_type_concept_id', full_name='DrugExposureInfo.drug_type_concept_id', index=5, number=6, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='drug_exposure_start_datetime', full_name='DrugExposureInfo.drug_exposure_start_datetime', index=6, number=7, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='drug_exposure_end_datetime', full_name='DrugExposureInfo.drug_exposure_end_datetime', index=7, number=8, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='verbatim_end_date', full_name='DrugExposureInfo.verbatim_end_date', index=8, number=9, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='stop_reason', full_name='DrugExposureInfo.stop_reason', index=9, number=10, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='refills', full_name='DrugExposureInfo.refills', index=10, number=11, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='quantity', full_name='DrugExposureInfo.quantity', index=11, number=12, type=2, cpp_type=6, label=1, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='days_supply', full_name='DrugExposureInfo.days_supply', index=12, number=13, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='sig', full_name='DrugExposureInfo.sig', index=13, number=14, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='route_concept_id', full_name='DrugExposureInfo.route_concept_id', index=14, number=15, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='lot_number', full_name='DrugExposureInfo.lot_number', index=15, number=16, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='provider_id', full_name='DrugExposureInfo.provider_id', index=16, number=17, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='visit_occurrence_id', full_name='DrugExposureInfo.visit_occurrence_id', index=17, number=18, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='visit_detail_id', full_name='DrugExposureInfo.visit_detail_id', index=18, number=19, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='drug_source_value', full_name='DrugExposureInfo.drug_source_value', index=19, number=20, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='drug_source_concept_id', full_name='DrugExposureInfo.drug_source_concept_id', index=20, number=21, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='route_source_value', full_name='DrugExposureInfo.route_source_value', index=21, number=22, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='dose_unit_source_value', full_name='DrugExposureInfo.dose_unit_source_value', index=22, number=23, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=2102, serialized_end=2717, ) _MEASUREMENTINFO = _descriptor.Descriptor( name='MeasurementInfo', full_name='MeasurementInfo', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='measurement_id', full_name='MeasurementInfo.measurement_id', index=0, number=1, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='person_id', full_name='MeasurementInfo.person_id', index=1, number=2, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='measurement_concept_id', full_name='MeasurementInfo.measurement_concept_id', index=2, number=3, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='measurement_date', full_name='MeasurementInfo.measurement_date', index=3, number=4, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='measurement_type_concept_id', full_name='MeasurementInfo.measurement_type_concept_id', index=4, number=5, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='measurement_datetime', full_name='MeasurementInfo.measurement_datetime', index=5, number=6, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='measurement_time', full_name='MeasurementInfo.measurement_time', index=6, number=7, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='operator_concept_id', full_name='MeasurementInfo.operator_concept_id', index=7, number=8, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='value_as_number', full_name='MeasurementInfo.value_as_number', index=8, number=9, type=2, cpp_type=6, label=1, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='value_as_concept_id', full_name='MeasurementInfo.value_as_concept_id', index=9, number=10, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='unit_concept_id', full_name='MeasurementInfo.unit_concept_id', index=10, number=11, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='range_low', full_name='MeasurementInfo.range_low', index=11, number=12, type=2, cpp_type=6, label=1, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='range_high', full_name='MeasurementInfo.range_high', index=12, number=13, type=2, cpp_type=6, label=1, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='provider_id', full_name='MeasurementInfo.provider_id', index=13, number=14, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='visit_occurrence_id', full_name='MeasurementInfo.visit_occurrence_id', index=14, number=15, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='visit_detail_id', full_name='MeasurementInfo.visit_detail_id', index=15, number=16, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='measurement_source_value', full_name='MeasurementInfo.measurement_source_value', index=16, number=17, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='measurement_source_concept_id', full_name='MeasurementInfo.measurement_source_concept_id', index=17, number=18, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='unit_source_value', full_name='MeasurementInfo.unit_source_value', index=18, number=19, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='value_source_value', full_name='MeasurementInfo.value_source_value', index=19, number=20, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=2720, serialized_end=3281, ) _OBSERVATIONPERIODINFO = _descriptor.Descriptor( name='ObservationPeriodInfo', full_name='ObservationPeriodInfo', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='observation_period_id', full_name='ObservationPeriodInfo.observation_period_id', index=0, number=1, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='person_id', full_name='ObservationPeriodInfo.person_id', index=1, number=2, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='observation_period_start_date', full_name='ObservationPeriodInfo.observation_period_start_date', index=2, number=3, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='observation_period_end_date', full_name='ObservationPeriodInfo.observation_period_end_date', index=3, number=4, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='period_type_concept_id', full_name='ObservationPeriodInfo.period_type_concept_id', index=4, number=5, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=3284, serialized_end=3465, ) _OBSERVATIONINFO = _descriptor.Descriptor( name='ObservationInfo', full_name='ObservationInfo', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='observation_id', full_name='ObservationInfo.observation_id', index=0, number=1, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='person_id', full_name='ObservationInfo.person_id', index=1, number=2, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='observation_concept_id', full_name='ObservationInfo.observation_concept_id', index=2, number=3, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='observation_date', full_name='ObservationInfo.observation_date', index=3, number=4, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='observation_type_concept_id', full_name='ObservationInfo.observation_type_concept_id', index=4, number=5, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='observation_datetime', full_name='ObservationInfo.observation_datetime', index=5, number=6, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='value_as_number', full_name='ObservationInfo.value_as_number', index=6, number=7, type=2, cpp_type=6, label=1, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='value_as_string', full_name='ObservationInfo.value_as_string', index=7, number=8, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='value_as_concept_id', full_name='ObservationInfo.value_as_concept_id', index=8, number=9, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='qualifier_concept_id', full_name='ObservationInfo.qualifier_concept_id', index=9, number=10, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='unit_concept_id', full_name='ObservationInfo.unit_concept_id', index=10, number=11, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='provider_id', full_name='ObservationInfo.provider_id', index=11, number=12, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='visit_occurrence_id', full_name='ObservationInfo.visit_occurrence_id', index=12, number=13, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='visit_detail_id', full_name='ObservationInfo.visit_detail_id', index=13, number=14, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='observation_source_value', full_name='ObservationInfo.observation_source_value', index=14, number=15, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='observation_source_concept_id', full_name='ObservationInfo.observation_source_concept_id', index=15, number=16, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='unit_source_value', full_name='ObservationInfo.unit_source_value', index=16, number=17, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='qualifier_source_value', full_name='ObservationInfo.qualifier_source_value', index=17, number=18, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=3468, serialized_end=3994, ) _PROCEDUREOCCURRENCEINFO = _descriptor.Descriptor( name='ProcedureOccurrenceInfo', full_name='ProcedureOccurrenceInfo', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='procedure_occurrence_id', full_name='ProcedureOccurrenceInfo.procedure_occurrence_id', index=0, number=1, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='person_id', full_name='ProcedureOccurrenceInfo.person_id', index=1, number=2, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='procedure_concept_id', full_name='ProcedureOccurrenceInfo.procedure_concept_id', index=2, number=3, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='procedure_date', full_name='ProcedureOccurrenceInfo.procedure_date', index=3, number=4, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='procedure_type_concept_id', full_name='ProcedureOccurrenceInfo.procedure_type_concept_id', index=4, number=5, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='procedure_datetime', full_name='ProcedureOccurrenceInfo.procedure_datetime', index=5, number=6, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='modifier_concept_id', full_name='ProcedureOccurrenceInfo.modifier_concept_id', index=6, number=7, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='quantity', full_name='ProcedureOccurrenceInfo.quantity', index=7, number=8, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='provider_id', full_name='ProcedureOccurrenceInfo.provider_id', index=8, number=9, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='visit_occurrence_id', full_name='ProcedureOccurrenceInfo.visit_occurrence_id', index=9, number=10, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='visit_detail_id', full_name='ProcedureOccurrenceInfo.visit_detail_id', index=10, number=11, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='procedure_source_value', full_name='ProcedureOccurrenceInfo.procedure_source_value', index=11, number=12, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='procedure_source_concept_id', full_name='ProcedureOccurrenceInfo.procedure_source_concept_id', index=12, number=13, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='modifier_source_value', full_name='ProcedureOccurrenceInfo.modifier_source_value', index=13, number=14, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=3997, serialized_end=4413, ) _VISITOCCURRENCEINFO = _descriptor.Descriptor( name='VisitOccurrenceInfo', full_name='VisitOccurrenceInfo', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='visit_occurrence_id', full_name='VisitOccurrenceInfo.visit_occurrence_id', index=0, number=1, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='person_id', full_name='VisitOccurrenceInfo.person_id', index=1, number=2, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='visit_concept_id', full_name='VisitOccurrenceInfo.visit_concept_id', index=2, number=3, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='visit_start_date', full_name='VisitOccurrenceInfo.visit_start_date', index=3, number=4, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='visit_end_date', full_name='VisitOccurrenceInfo.visit_end_date', index=4, number=5, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='visit_type_concept_id', full_name='VisitOccurrenceInfo.visit_type_concept_id', index=5, number=6, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='visit_start_datetime', full_name='VisitOccurrenceInfo.visit_start_datetime', index=6, number=7, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='visit_end_datetime', full_name='VisitOccurrenceInfo.visit_end_datetime', index=7, number=8, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='provider_id', full_name='VisitOccurrenceInfo.provider_id', index=8, number=9, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='care_site_id', full_name='VisitOccurrenceInfo.care_site_id', index=9, number=10, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='visit_source_value', full_name='VisitOccurrenceInfo.visit_source_value', index=10, number=11, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='visit_source_concept_id', full_name='VisitOccurrenceInfo.visit_source_concept_id', index=11, number=12, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='admitting_source_concept_id', full_name='VisitOccurrenceInfo.admitting_source_concept_id', index=12, number=13, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='admitting_source_value', full_name='VisitOccurrenceInfo.admitting_source_value', index=13, number=14, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='discharge_to_concept_id', full_name='VisitOccurrenceInfo.discharge_to_concept_id', index=14, number=15, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='discharge_to_source_value', full_name='VisitOccurrenceInfo.discharge_to_source_value', index=15, number=16, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='preceding_visit_occurrence_id', full_name='VisitOccurrenceInfo.preceding_visit_occurrence_id', index=16, number=17, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=4416, serialized_end=4930, ) _REQUESTCOMPARISON = _descriptor.Descriptor( name='RequestComparison', full_name='RequestComparison', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='comparison_id', full_name='RequestComparison.comparison_id', index=0, number=1, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=4932, serialized_end=4974, ) _COMPARISONCOHORTINFO = _descriptor.Descriptor( name='ComparisonCohortInfo', full_name='ComparisonCohortInfo', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='id', full_name='ComparisonCohortInfo.id', index=0, number=1, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='name', full_name='ComparisonCohortInfo.name', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='person_count', full_name='ComparisonCohortInfo.person_count', index=2, number=3, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=4976, serialized_end=5046, ) _COMPARISONROWINFO = _descriptor.Descriptor( name='ComparisonRowInfo', full_name='ComparisonRowInfo', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='category1', full_name='ComparisonRowInfo.category1', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='category2', full_name='ComparisonRowInfo.category2', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='values', full_name='ComparisonRowInfo.values', index=2, number=3, type=9, cpp_type=9, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='p_value', full_name='ComparisonRowInfo.p_value', index=3, number=4, type=2, cpp_type=6, label=1, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='p_value_is_group', full_name='ComparisonRowInfo.p_value_is_group', index=4, number=5, type=8, cpp_type=7, label=1, has_default_value=False, default_value=False, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=5048, serialized_end=5164, ) _RESPONSECOMPARISON = _descriptor.Descriptor( name='ResponseComparison', full_name='ResponseComparison', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='name', full_name='ResponseComparison.name', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='cohort_list', full_name='ResponseComparison.cohort_list', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='row_list', full_name='ResponseComparison.row_list', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=5166, serialized_end=5282, ) _RESPONSECOHORTLIST.fields_by_name['cohort_list'].message_type = _COHORTINFO _RESPONSECOMPARISON.fields_by_name['cohort_list'].message_type = _COMPARISONCOHORTINFO _RESPONSECOMPARISON.fields_by_name['row_list'].message_type = _COMPARISONROWINFO DESCRIPTOR.message_types_by_name['RequestLogin'] = _REQUESTLOGIN DESCRIPTOR.message_types_by_name['ResponseLogin'] = _RESPONSELOGIN DESCRIPTOR.message_types_by_name['RequestCohortList'] = _REQUESTCOHORTLIST DESCRIPTOR.message_types_by_name['CohortInfo'] = _COHORTINFO DESCRIPTOR.message_types_by_name['ResponseCohortList'] = _RESPONSECOHORTLIST DESCRIPTOR.message_types_by_name['RequestCohortStream'] = _REQUESTCOHORTSTREAM DESCRIPTOR.message_types_by_name['PersonInfo'] = _PERSONINFO DESCRIPTOR.message_types_by_name['ConditionOccurrenceInfo'] = _CONDITIONOCCURRENCEINFO DESCRIPTOR.message_types_by_name['DeathInfo'] = _DEATHINFO DESCRIPTOR.message_types_by_name['DeviceExposureInfo'] = _DEVICEEXPOSUREINFO DESCRIPTOR.message_types_by_name['DrugExposureInfo'] = _DRUGEXPOSUREINFO DESCRIPTOR.message_types_by_name['MeasurementInfo'] = _MEASUREMENTINFO DESCRIPTOR.message_types_by_name['ObservationPeriodInfo'] = _OBSERVATIONPERIODINFO DESCRIPTOR.message_types_by_name['ObservationInfo'] = _OBSERVATIONINFO DESCRIPTOR.message_types_by_name['ProcedureOccurrenceInfo'] = _PROCEDUREOCCURRENCEINFO DESCRIPTOR.message_types_by_name['VisitOccurrenceInfo'] = _VISITOCCURRENCEINFO DESCRIPTOR.message_types_by_name['RequestComparison'] = _REQUESTCOMPARISON DESCRIPTOR.message_types_by_name['ComparisonCohortInfo'] = _COMPARISONCOHORTINFO DESCRIPTOR.message_types_by_name['ComparisonRowInfo'] = _COMPARISONROWINFO DESCRIPTOR.message_types_by_name['ResponseComparison'] = _RESPONSECOMPARISON _sym_db.RegisterFileDescriptor(DESCRIPTOR) RequestLogin = _reflection.GeneratedProtocolMessageType('RequestLogin', (_message.Message,), { 'DESCRIPTOR' : _REQUESTLOGIN, '__module__' : 'clue_pb2' # @@protoc_insertion_point(class_scope:RequestLogin) }) _sym_db.RegisterMessage(RequestLogin) ResponseLogin = _reflection.GeneratedProtocolMessageType('ResponseLogin', (_message.Message,), { 'DESCRIPTOR' : _RESPONSELOGIN, '__module__' : 'clue_pb2' # @@protoc_insertion_point(class_scope:ResponseLogin) }) _sym_db.RegisterMessage(ResponseLogin) RequestCohortList = _reflection.GeneratedProtocolMessageType('RequestCohortList', (_message.Message,), { 'DESCRIPTOR' : _REQUESTCOHORTLIST, '__module__' : 'clue_pb2' # @@protoc_insertion_point(class_scope:RequestCohortList) }) _sym_db.RegisterMessage(RequestCohortList) CohortInfo = _reflection.GeneratedProtocolMessageType('CohortInfo', (_message.Message,), { 'DESCRIPTOR' : _COHORTINFO, '__module__' : 'clue_pb2' # @@protoc_insertion_point(class_scope:CohortInfo) }) _sym_db.RegisterMessage(CohortInfo) ResponseCohortList = _reflection.GeneratedProtocolMessageType('ResponseCohortList', (_message.Message,), { 'DESCRIPTOR' : _RESPONSECOHORTLIST, '__module__' : 'clue_pb2' # @@protoc_insertion_point(class_scope:ResponseCohortList) }) _sym_db.RegisterMessage(ResponseCohortList) RequestCohortStream = _reflection.GeneratedProtocolMessageType('RequestCohortStream', (_message.Message,), { 'DESCRIPTOR' : _REQUESTCOHORTSTREAM, '__module__' : 'clue_pb2' # @@protoc_insertion_point(class_scope:RequestCohortStream) }) _sym_db.RegisterMessage(RequestCohortStream) PersonInfo = _reflection.GeneratedProtocolMessageType('PersonInfo', (_message.Message,), { 'DESCRIPTOR' : _PERSONINFO, '__module__' : 'clue_pb2' # @@protoc_insertion_point(class_scope:PersonInfo) }) _sym_db.RegisterMessage(PersonInfo) ConditionOccurrenceInfo = _reflection.GeneratedProtocolMessageType('ConditionOccurrenceInfo', (_message.Message,), { 'DESCRIPTOR' : _CONDITIONOCCURRENCEINFO, '__module__' : 'clue_pb2' # @@protoc_insertion_point(class_scope:ConditionOccurrenceInfo) }) _sym_db.RegisterMessage(ConditionOccurrenceInfo) DeathInfo = _reflection.GeneratedProtocolMessageType('DeathInfo', (_message.Message,), { 'DESCRIPTOR' : _DEATHINFO, '__module__' : 'clue_pb2' # @@protoc_insertion_point(class_scope:DeathInfo) }) _sym_db.RegisterMessage(DeathInfo) DeviceExposureInfo = _reflection.GeneratedProtocolMessageType('DeviceExposureInfo', (_message.Message,), { 'DESCRIPTOR' : _DEVICEEXPOSUREINFO, '__module__' : 'clue_pb2' # @@protoc_insertion_point(class_scope:DeviceExposureInfo) }) _sym_db.RegisterMessage(DeviceExposureInfo) DrugExposureInfo = _reflection.GeneratedProtocolMessageType('DrugExposureInfo', (_message.Message,), { 'DESCRIPTOR' : _DRUGEXPOSUREINFO, '__module__' : 'clue_pb2' # @@protoc_insertion_point(class_scope:DrugExposureInfo) }) _sym_db.RegisterMessage(DrugExposureInfo) MeasurementInfo = _reflection.GeneratedProtocolMessageType('MeasurementInfo', (_message.Message,), { 'DESCRIPTOR' : _MEASUREMENTINFO, '__module__' : 'clue_pb2' # @@protoc_insertion_point(class_scope:MeasurementInfo) }) _sym_db.RegisterMessage(MeasurementInfo) ObservationPeriodInfo = _reflection.GeneratedProtocolMessageType('ObservationPeriodInfo', (_message.Message,), { 'DESCRIPTOR' : _OBSERVATIONPERIODINFO, '__module__' : 'clue_pb2' # @@protoc_insertion_point(class_scope:ObservationPeriodInfo) }) _sym_db.RegisterMessage(ObservationPeriodInfo) ObservationInfo = _reflection.GeneratedProtocolMessageType('ObservationInfo', (_message.Message,), { 'DESCRIPTOR' : _OBSERVATIONINFO, '__module__' : 'clue_pb2' # @@protoc_insertion_point(class_scope:ObservationInfo) }) _sym_db.RegisterMessage(ObservationInfo) ProcedureOccurrenceInfo = _reflection.GeneratedProtocolMessageType('ProcedureOccurrenceInfo', (_message.Message,), { 'DESCRIPTOR' : _PROCEDUREOCCURRENCEINFO, '__module__' : 'clue_pb2' # @@protoc_insertion_point(class_scope:ProcedureOccurrenceInfo) }) _sym_db.RegisterMessage(ProcedureOccurrenceInfo) VisitOccurrenceInfo = _reflection.GeneratedProtocolMessageType('VisitOccurrenceInfo', (_message.Message,), { 'DESCRIPTOR' : _VISITOCCURRENCEINFO, '__module__' : 'clue_pb2' # @@protoc_insertion_point(class_scope:VisitOccurrenceInfo) }) _sym_db.RegisterMessage(VisitOccurrenceInfo) RequestComparison = _reflection.GeneratedProtocolMessageType('RequestComparison', (_message.Message,), { 'DESCRIPTOR' : _REQUESTCOMPARISON, '__module__' : 'clue_pb2' # @@protoc_insertion_point(class_scope:RequestComparison) }) _sym_db.RegisterMessage(RequestComparison) ComparisonCohortInfo = _reflection.GeneratedProtocolMessageType('ComparisonCohortInfo', (_message.Message,), { 'DESCRIPTOR' : _COMPARISONCOHORTINFO, '__module__' : 'clue_pb2' # @@protoc_insertion_point(class_scope:ComparisonCohortInfo) }) _sym_db.RegisterMessage(ComparisonCohortInfo) ComparisonRowInfo = _reflection.GeneratedProtocolMessageType('ComparisonRowInfo', (_message.Message,), { 'DESCRIPTOR' : _COMPARISONROWINFO, '__module__' : 'clue_pb2' # @@protoc_insertion_point(class_scope:ComparisonRowInfo) }) _sym_db.RegisterMessage(ComparisonRowInfo) ResponseComparison = _reflection.GeneratedProtocolMessageType('ResponseComparison', (_message.Message,), { 'DESCRIPTOR' : _RESPONSECOMPARISON, '__module__' : 'clue_pb2' # @@protoc_insertion_point(class_scope:ResponseComparison) }) _sym_db.RegisterMessage(ResponseComparison) _CLUE = _descriptor.ServiceDescriptor( name='CLUE', full_name='CLUE', file=DESCRIPTOR, index=0, serialized_options=None, create_key=_descriptor._internal_create_key, serialized_start=5285, serialized_end=6251, methods=[ _descriptor.MethodDescriptor( name='AuthLogin', full_name='CLUE.AuthLogin', index=0, containing_service=None, input_type=_REQUESTLOGIN, output_type=_RESPONSELOGIN, serialized_options=None, create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='GetCohortList', full_name='CLUE.GetCohortList', index=1, containing_service=None, input_type=_REQUESTCOHORTLIST, output_type=_RESPONSECOHORTLIST, serialized_options=None, create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='GetCohortPersonTable', full_name='CLUE.GetCohortPersonTable', index=2, containing_service=None, input_type=_REQUESTCOHORTSTREAM, output_type=_PERSONINFO, serialized_options=None, create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='GetCohortConditionOccurrenceTable', full_name='CLUE.GetCohortConditionOccurrenceTable', index=3, containing_service=None, input_type=_REQUESTCOHORTSTREAM, output_type=_CONDITIONOCCURRENCEINFO, serialized_options=None, create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='GetCohortDeathTable', full_name='CLUE.GetCohortDeathTable', index=4, containing_service=None, input_type=_REQUESTCOHORTSTREAM, output_type=_DEATHINFO, serialized_options=None, create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='GetCohortDeviceExposureTable', full_name='CLUE.GetCohortDeviceExposureTable', index=5, containing_service=None, input_type=_REQUESTCOHORTSTREAM, output_type=_DEVICEEXPOSUREINFO, serialized_options=None, create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='GetCohortDrugExposureTable', full_name='CLUE.GetCohortDrugExposureTable', index=6, containing_service=None, input_type=_REQUESTCOHORTSTREAM, output_type=_DRUGEXPOSUREINFO, serialized_options=None, create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='GetCohortMeasurementTable', full_name='CLUE.GetCohortMeasurementTable', index=7, containing_service=None, input_type=_REQUESTCOHORTSTREAM, output_type=_MEASUREMENTINFO, serialized_options=None, create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='GetCohortObservationPeriodTable', full_name='CLUE.GetCohortObservationPeriodTable', index=8, containing_service=None, input_type=_REQUESTCOHORTSTREAM, output_type=_OBSERVATIONPERIODINFO, serialized_options=None, create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='GetCohortObservationTable', full_name='CLUE.GetCohortObservationTable', index=9, containing_service=None, input_type=_REQUESTCOHORTSTREAM, output_type=_OBSERVATIONINFO, serialized_options=None, create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='GetCohortProcedureOccurrenceTable', full_name='CLUE.GetCohortProcedureOccurrenceTable', index=10, containing_service=None, input_type=_REQUESTCOHORTSTREAM, output_type=_PROCEDUREOCCURRENCEINFO, serialized_options=None, create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='GetCohortVisitOccurrenceTable', full_name='CLUE.GetCohortVisitOccurrenceTable', index=11, containing_service=None, input_type=_REQUESTCOHORTSTREAM, output_type=_VISITOCCURRENCEINFO, serialized_options=None, create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='GetCohortComparison', full_name='CLUE.GetCohortComparison', index=12, containing_service=None, input_type=_REQUESTCOMPARISON, output_type=_RESPONSECOMPARISON, serialized_options=None, create_key=_descriptor._internal_create_key, ), ]) _sym_db.RegisterServiceDescriptor(_CLUE) DESCRIPTOR.services_by_name['CLUE'] = _CLUE # @@protoc_insertion_point(module_scope)

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Python

gulinalg/tests/test_decomposition.py

amit-r/gulinalg

d63c46fcb655b89b08ae438bb7dbd277675d5b14

[ "BSD-2-Clause" ]

11

2015-04-08T13:44:00.000Z

2020-11-03T04:21:50.000Z

gulinalg/tests/test_decomposition.py

amit-r/gulinalg

d63c46fcb655b89b08ae438bb7dbd277675d5b14

[ "BSD-2-Clause" ]

4

2017-07-21T05:15:44.000Z

2020-11-12T15:36:11.000Z

gulinalg/tests/test_decomposition.py

amit-r/gulinalg

d63c46fcb655b89b08ae438bb7dbd277675d5b14

[ "BSD-2-Clause" ]

13

2015-03-30T04:33:26.000Z

2021-02-22T18:24:26.000Z

""" Tests different implementations of decomposition functions. """ from __future__ import print_function from unittest import TestCase, skipIf import numpy as np from numpy.testing import run_module_suite, assert_allclose from pkg_resources import parse_version import gulinalg class TestLU(TestCase): """ Test LU decomposition. """ def test_lu_m_gt_n(self): """LU decompose a matrix where dimension m > n""" a = np.ascontiguousarray(np.random.randn(75, 50)) p, l, u = gulinalg.lu(a) assert_allclose(np.dot(np.dot(p, l), u), a) def test_lu_m_lt_n(self): """LU decompose a matrix where dimension m < n""" a = np.ascontiguousarray(np.random.randn(50, 75)) p, l, u = gulinalg.lu(a) assert_allclose(np.dot(np.dot(p, l), u), a) @skipIf(parse_version(np.__version__) < parse_version('1.13'), "Prior to 1.13, numpy low level iterators didn't support removing " "empty axis. So gufunc couldn't be called with empty inner loop") def test_lu_m_and_n_zero(self): """Corner case of decomposing where m = 0 and n = 0""" a = np.ascontiguousarray(np.random.randn(0, 0)) p, l, u = gulinalg.lu(a) # p is MxM, l is MxK, u is KxN where K = min(M, N) # As M = 0 here, all three of them should be empty. assert p.shape == (0, 0) assert l.shape == (0, 0) assert u.shape == (0, 0) assert_allclose(np.dot(np.dot(p, l), u), a) @skipIf(parse_version(np.__version__) < parse_version('1.13'), "Prior to 1.13, numpy low level iterators didn't support removing " "empty axis. So gufunc couldn't be called with empty inner loop") def test_lu_m_zero(self): """Corner case of decomposing where m = 0""" a = np.ascontiguousarray(np.random.randn(0, 2)) p, l, u = gulinalg.lu(a) # p is MxM, l is MxK, u is KxN where K = min(M, N) # As M = 0 here, all three of them should be empty. assert p.shape == (0, 0) assert l.shape == (0, 0) assert u.shape == (0, 2) assert_allclose(np.dot(np.dot(p, l), u), a) @skipIf(parse_version(np.__version__) < parse_version('1.13'), "Prior to 1.13, numpy low level iterators didn't support removing " "empty axis. So gufunc couldn't be called with empty inner loop") def test_lu_n_zero(self): """Corner case of decomposing where n = 0""" a = np.ascontiguousarray(np.random.randn(2, 0)) p, l, u = gulinalg.lu(a) # p is MxM, l is MxK, u is KxN where K = min(M, N) # As N = 0 here, assert following dimensions. assert p.shape == (2, 2) assert l.shape == (2, 0) assert u.shape == (0, 0) assert_allclose(np.dot(np.dot(p, l), u), a) def test_lu_size_one_matrix(self): """Corner case of decomposing size 1 matrix""" a = np.ascontiguousarray(np.random.randn(1, 1)) p, l, u = gulinalg.lu(a) assert_allclose(np.dot(np.dot(p, l), u), a) def test_lu_permute_m_gt_n(self): """LU decompose a matrix where dimension m > n""" a = np.ascontiguousarray(np.random.randn(75, 50)) pl, u = gulinalg.lu(a, permute_l=True) assert_allclose(np.dot(pl, u), a) def test_lu_permute_m_lt_n(self): """LU decompose a matrix where dimension m < n""" a = np.ascontiguousarray(np.random.randn(50, 75)) pl, u = gulinalg.lu(a, permute_l=True) assert_allclose(np.dot(pl, u), a) def test_lu_permute_size_1_matrix(self): a = np.ascontiguousarray(np.random.randn(1, 1)) pl, u = gulinalg.lu(a, permute_l=True) assert_allclose(np.dot(pl, u), a) def test_complex_numbers(self): """Test for complex numbers input.""" a = np.array([[1 + 2j, 3 + 4j], [5 + 6j, 7 + -8j]]) p, l, u = gulinalg.lu(a) assert_allclose(np.dot(np.dot(p, l), u), a) def test_fortran_layout_matrix(self): """Input matrix is fortran layout matrix""" a = np.asfortranarray(np.random.randn(75, 50)) pl, u = gulinalg.lu(a, permute_l=True) assert_allclose(np.dot(pl, u), a) def test_input_matrix_non_contiguous(self): """Input matrix is not a contiguous matrix""" a = np.ascontiguousarray(np.random.randn(50, 75, 2))[:, :, 0] assert not a.flags.c_contiguous and not a.flags.f_contiguous p, l, u = gulinalg.lu(a) assert_allclose(np.dot(np.dot(p, l), u), a) def test_vector(self): """test vectorized LU decomposition""" a = np.ascontiguousarray(np.random.randn(10, 75, 50)) p, l, u = gulinalg.lu(a) res = np.stack([np.dot(np.dot(p[i], l[i]), u[i]) for i in range(len(a))]) assert_allclose(res, a) @skipIf(parse_version(np.__version__) < parse_version('1.13'), "Prior to 1.13, numpy low level iterators didn't support removing " "empty axis. So gufunc couldn't be called with empty inner loop") def test_vector_m_and_n_zero(self): """Corner case of decomposing where m = 0 and n = 0""" a = np.ascontiguousarray(np.random.randn(10, 0, 0)) p, l, u = gulinalg.lu(a) # p is MxM, l is MxK, u is KxN where K = min(M, N) # As M = 0 here, all three of them should be empty. assert p.shape == (10, 0, 0) assert l.shape == (10, 0, 0) assert u.shape == (10, 0, 0) res = np.stack([np.dot(np.dot(p[i], l[i]), u[i]) for i in range(len(a))]) assert_allclose(res, a) @skipIf(parse_version(np.__version__) < parse_version('1.13'), "Prior to 1.13, numpy low level iterators didn't support removing " "empty axis. So gufunc couldn't be called with empty inner loop") def test_vector_m_zero(self): """Corner case of decomposing where m = 0""" a = np.ascontiguousarray(np.random.randn(10, 0, 2)) p, l, u = gulinalg.lu(a) # p is MxM, l is MxK, u is KxN where K = min(M, N) # As M = 0 here, all three of them should be empty. assert p.shape == (10, 0, 0) assert l.shape == (10, 0, 0) assert u.shape == (10, 0, 2) res = np.stack([np.dot(np.dot(p[i], l[i]), u[i]) for i in range(len(a))]) assert_allclose(res, a) @skipIf(parse_version(np.__version__) < parse_version('1.13'), "Prior to 1.13, numpy low level iterators didn't support removing " "empty axis. So gufunc couldn't be called with empty inner loop") def test_vector_n_zero(self): """Corner case of decomposing where n = 0""" a = np.ascontiguousarray(np.random.randn(10, 2, 0)) p, l, u = gulinalg.lu(a) # p is MxM, l is MxK, u is KxN where K = min(M, N) # As N = 0 here, assert following dimensions. assert p.shape == (10, 2, 2) assert l.shape == (10, 2, 0) assert u.shape == (10, 0, 0) res = np.stack([np.dot(np.dot(p[i], l[i]), u[i]) for i in range(len(a))]) assert_allclose(res, a) def test_vector_size_one_matrix(self): """Corner case of decomposing size 1 matrix""" a = np.ascontiguousarray(np.random.randn(10, 1, 1)) p, l, u = gulinalg.lu(a) res = np.stack([np.dot(np.dot(p[i], l[i]), u[i]) for i in range(len(a))]) assert_allclose(res, a) def test_nan_handling(self): """NaN in one output shouldn't contaminate remaining outputs""" a = np.array([[[3, 4, 5], [2, np.nan, 3]], [[3, 4, 5], [2, 1, 3]]]) pl, u = gulinalg.lu(a, permute_l=True) ref_pl = np.array([[[1., 0.], [0.66666667, 1.]], [[1., 0.], [0.66666667, 1.]]]) ref_u = np.array([[[3., 4., 5.], [0., np.nan, -0.33333333]], [[3., 4., 5.], [0., -1.66666667, -0.33333333]]]) assert_allclose(pl, ref_pl) assert_allclose(u, ref_u) def test_infinity_handling(self): """Infinity in one output shouldn't contaminate remaining outputs""" a = np.array([[[3, 4, 5], [2, np.inf, 3]], [[3, 4, 5], [2, 1, 3]]]) pl, u = gulinalg.lu(a, permute_l=True) ref_pl = np.array([[[1., 0.], [0.66666667, 1.]], [[1., 0.], [0.66666667, 1.]]]) ref_u = np.array([[[3., 4., 5.], [0., np.inf, -0.33333333]], [[3., 4., 5.], [0., -1.66666667, -0.33333333]]]) assert_allclose(pl, ref_pl) assert_allclose(u, ref_u) class TestQR(TestCase): """Test QR decomposition""" def test_m_lt_n(self): """For M < N, return full MxM Q matrix and all M rows of R.""" m = 50 n = 75 a = np.ascontiguousarray(np.random.randn(m, n)) q, r = gulinalg.qr(a) assert_allclose(np.dot(q, q.T), np.identity(m), atol=1e-15) assert_allclose(np.dot(q, r), a) def test_m_gt_n(self): """For M > N, return full MxM Q matrix and all M rows of R.""" m = 75 n = 50 a = np.ascontiguousarray(np.random.randn(m, n)) q, r = gulinalg.qr(a) assert q.shape == (m, m) assert r.shape == (m, n) assert_allclose(np.dot(q, q.T), np.identity(m), atol=1e-15) assert_allclose(np.dot(q, r), a) def test_m_gt_n_economy(self): """ If M > N, economy mode returns only N columns for Q and N rows for R. """ m = 75 n = 50 a = np.ascontiguousarray(np.random.randn(m, n)) q, r = gulinalg.qr(a, economy=True) assert q.shape == (m, n) assert r.shape == (n, n) assert_allclose(np.dot(q, r), a) @skipIf(parse_version(np.__version__) < parse_version('1.13'), "Prior to 1.13, numpy low level iterators didn't support removing " "empty axis. So gufunc couldn't be called with empty inner loop") def test_m_and_n_zero(self): """Corner case of decomposing where m = 0 and n = 0""" a = np.ascontiguousarray(np.random.randn(0, 0)) q, r = gulinalg.qr(a) # q is MxM or MxK (economy mode) and r is MxN or KxN (economy mode) # where K = min(M, N). As M = 0, K = 0. so q and r should be empty. assert q.shape == (0, 0) assert r.shape == (0, 0) assert_allclose(np.dot(q, r), a) @skipIf(parse_version(np.__version__) < parse_version('1.13'), "Prior to 1.13, numpy low level iterators didn't support removing " "empty axis. So gufunc couldn't be called with empty inner loop") def test_m_zero(self): """Corner case of decomposing where m = 0""" a = np.ascontiguousarray(np.random.randn(0, 2)) q, r = gulinalg.qr(a) # q is MxM or MxK (economy mode) and r is MxN or KxN (economy mode) # where K = min(M, N). assert q.shape == (0, 0) assert r.shape == (0, 2) assert_allclose(np.dot(q, r), a) @skipIf(parse_version(np.__version__) < parse_version('1.13'), "Prior to 1.13, numpy low level iterators didn't support removing " "empty axis. So gufunc couldn't be called with empty inner loop") def test_n_zero(self): """Corner case of decomposing where n = 0""" a = np.ascontiguousarray(np.random.randn(2, 0)) q, r = gulinalg.qr(a) # q is MxM or MxK (economy mode) and r is MxN or KxN (economy mode) # where K = min(M, N). assert q.shape == (2, 2) assert r.shape == (2, 0) assert_allclose(np.dot(q, r), a) def test_qr_size_one_matrix(self): """Corner case of decomposing size 1 matrix""" m = 1 n = 1 a = np.ascontiguousarray(np.random.randn(m, n)) q, r = gulinalg.qr(a) assert q.shape == (m, n) assert r.shape == (n, n) assert_allclose(np.dot(q, r), a) def test_complex_numbers(self): """Test for complex numbers input.""" a = np.array([[1 + 2j, 3 + 4j], [5 + 6j, 7 + -8j]]) q, r = gulinalg.qr(a) assert_allclose(np.dot(q, r), a) def test_fortran_layout_matrix(self): """Input matrix is fortran layout matrix""" m = 75 n = 50 a = np.asfortranarray(np.random.randn(m, n)) q, r = gulinalg.qr(a, economy=True) assert q.shape == (m, n) assert r.shape == (n, n) assert_allclose(np.dot(q, r), a) def test_input_matrix_non_contiguous(self): """Input matrix is not a contiguous matrix""" m = 75 n = 50 a = np.ascontiguousarray(np.random.randn(m, n, 2))[:, :, 0] assert not a.flags.c_contiguous and not a.flags.f_contiguous q, r = gulinalg.qr(a, economy=True) assert q.shape == (m, n) assert r.shape == (n, n) assert_allclose(np.dot(q, r), a) def test_vector(self): """test vectorized QR decomposition""" a = np.ascontiguousarray(np.random.randn(10, 75, 50)) q, r = gulinalg.qr(a) res = np.stack([np.dot(q[i], r[i]) for i in range(len(a))]) assert_allclose(res, a) @skipIf(parse_version(np.__version__) < parse_version('1.13'), "Prior to 1.13, numpy low level iterators didn't support removing " "empty axis. So gufunc couldn't be called with empty inner loop") def test_vector_m_and_n_zero(self): """Corner case of decomposing where m = 0 and n = 0""" a = np.ascontiguousarray(np.random.randn(10, 0, 0)) q, r = gulinalg.qr(a) # q is MxM or MxK (economy mode) and r is MxN or KxN (economy mode) # where K = min(M, N). As M = 0, K = 0. so q and r should be empty. assert q.shape == (10, 0, 0) assert r.shape == (10, 0, 0) res = np.stack([np.dot(q[i], r[i]) for i in range(len(a))]) assert_allclose(res, a) @skipIf(parse_version(np.__version__) < parse_version('1.13'), "Prior to 1.13, numpy low level iterators didn't support removing " "empty axis. So gufunc couldn't be called with empty inner loop") def test_vector_m_zero(self): """Corner case of decomposing where m = 0""" a = np.ascontiguousarray(np.random.randn(10, 0, 2)) q, r = gulinalg.qr(a) # q is MxM or MxK (economy mode) and r is MxN or KxN (economy mode) # where K = min(M, N). assert q.shape == (10, 0, 0) assert r.shape == (10, 0, 2) res = np.stack([np.dot(q[i], r[i]) for i in range(len(a))]) assert_allclose(res, a) @skipIf(parse_version(np.__version__) < parse_version('1.13'), "Prior to 1.13, numpy low level iterators didn't support removing " "empty axis. So gufunc couldn't be called with empty inner loop") def test_vector_n_zero(self): """Corner case of decomposing where n = 0""" a = np.ascontiguousarray(np.random.randn(10, 2, 0)) q, r = gulinalg.qr(a) # q is MxM or MxK (economy mode) and r is MxN or KxN (economy mode) # where K = min(M, N). assert q.shape == (10, 2, 2) assert r.shape == (10, 2, 0) res = np.stack([np.dot(q[i], r[i]) for i in range(len(a))]) assert_allclose(res, a) def test_vector_size_one_matrices(self): """Corner case of decomposing where m = 1 and n = 1""" a = np.ascontiguousarray(np.random.randn(10, 1, 1)) q, r = gulinalg.qr(a) # q is MxM or MxK (economy mode) and r is MxN or KxN (economy mode) # where K = min(M, N). As M = 0, K = 0. so q and r should be empty. assert q.shape == (10, 1, 1) assert r.shape == (10, 1, 1) res = np.stack([np.dot(q[i], r[i]) for i in range(len(a))]) assert_allclose(res, a) def test_nan_handling(self): """NaN in one output shouldn't contaminate remaining outputs""" a = np.array([[[3, 4, 5], [np.nan, 1, 3]], [[3, 4, 5], [2, 1, 3]]]) q, r = gulinalg.qr(a) ref_q = np.array([[-0.83205029, -0.5547002], [-0.5547002, 0.83205029]]) ref_r = np.array([[-3.60555128, -3.88290137, -5.82435206], [0., -1.38675049, -0.2773501]]) # For NaN input i.e. a[0], expected output in ATLAS, MKL and SCIPY is: # [[nan, nan], [nan, nan]] # However openblas output is: # [[nan, 0], [nan, 1]]. # As this test checks that nan in one input should not impact output # for second input matrix, comparing output for second is enough. assert_allclose(q[1], ref_q) assert_allclose(r[1], ref_r) def test_infinity_handling(self): """Infinity in one output shouldn't contaminate remaining outputs""" a = np.array([[[3, 4, 5], [np.inf, 1, 3]], [[3, 4, 5], [2, 1, 3]]]) q, r = gulinalg.qr(a) ref_q = np.array([[-0.83205029, -0.5547002], [-0.5547002, 0.83205029]]) ref_r = np.array([[-3.60555128, -3.88290137, -5.82435206], [0., -1.38675049, -0.2773501]]) # For infinity input i.e. a[0], expected output in ATLAS, MKL and SCIPY # is: [[nan, nan], [nan, nan]] # However openblas output is: # [[-0.707107, nan], [nan, nan]]. # As this test checks that infinity in one input should not impact # output for second input, comparing output for second is enough. assert_allclose(q[1], ref_q) assert_allclose(r[1], ref_r) if __name__ == '__main__': run_module_suite()

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null

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7

d0932198a6cb6949a2e03b3b3f004f15b7c9abe6

177

py

Python

drfx/PyPortal/views.py

amarshukla/DRF-CustomUser-AuthToken

a19e8c963d9ef4ad5e8359556f0212ca60995a42

[ "MIT" ]

null

drfx/PyPortal/views.py

amarshukla/DRF-CustomUser-AuthToken

a19e8c963d9ef4ad5e8359556f0212ca60995a42

[ "MIT" ]

null

drfx/PyPortal/views.py

amarshukla/DRF-CustomUser-AuthToken

a19e8c963d9ef4ad5e8359556f0212ca60995a42

[ "MIT" ]

null

from django.http import HttpResponse def home(request): return HttpResponse('<!DOCTYPE html> <html> <body> <h1> <center>Custom User Model</center> </h1> </body> </html>')

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d0af4fe8d7d8ffc6a442202242ba7cdf84bf0191

110,164

py

Python

restservice/tests/test_cases.py

CenturyLink/ExpertDHCP

4dbcd36da7468b9a95a7869df19172fe890cefd2

[ "MIT" ]

1

2022-03-08T00:38:33.000Z

restservice/tests/test_cases.py

aaronlumen/ExpertDHCP

4dbcd36da7468b9a95a7869df19172fe890cefd2

[ "MIT" ]

null

restservice/tests/test_cases.py

aaronlumen/ExpertDHCP

4dbcd36da7468b9a95a7869df19172fe890cefd2

[ "MIT" ]

2

2022-02-11T17:13:48.000Z

2022-03-08T00:36:03.000Z

import unittest import json from restservice import LOGGER, create_app from restservice.endpoints import ERROR_4001_VALUE, ERROR_4006_VALUE, \ ERROR_4005_VALUE, ERROR_4008_VALUE, ERROR_4011_VALUE, ERROR_4014_VALUE, \ ERROR_4020_VALUE, ERROR_4018_VALUE, ERROR_4012_VALUE, ERROR_4015_VALUE, \ ERROR_4003_VALUE, ERROR_4019_VALUE, ERROR_4007_VALUE, ERROR_4016_VALUE from restservice.config import GIT_BACKUP, KEA_SERVER_BACKUP, BACKUP_CONFIG, \ SUBNETS_NOT_FOUND, SUBNET_NOT_FOUND, DHCP_IP, TEST_LOGGING, \ DHCP_PORT, RESERVATION_NOT_FOUND, OPTIONS_NOT_FOUND from restservice.tests.test_config import config_pt, config_nt from restservice.tests.test_utilities import get_num_reservations, get_num_subnets, \ get_len_subnet_reserv_options_by_id_and_mac, get_len_subnet_options_by_id class PositiveTests(unittest.TestCase): """ Test Cases - Positive """ def setUp(self): """ Creating the test client using the create app from init """ test_app = create_app() self.app = test_app.test_client() def test_01_main_page(self): """ Testing the /dhcp4 path which should just return DHCP Based provisioning as data in response API Path: /dhcp4 API Code: 001 API Function Name: fast_dhcp.endpoints.home Passes only if all of the following are true: 1. Response data is DHCP BASED PROVISIONING. 2. FAST Type Response statusCode is 9000011000 3. FAST Type Response statusValue is 'Command execution successful' 4. Response status code is 200 """ LOGGER.info('Testing home()') response = self.app.get('/dhcp4', follow_redirects=True) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) self.assertEqual(response.status_code, 200) self.assertEqual(api_response_json['statusCode'], '9000011000') self.assertEqual(api_response_json['statusValue'], "Command execution successful") self.assertEqual(api_response_json['data']['title'], 'DHCP BASED PROVISIONING') def test_02_get_kea_config(self): """ Testing the get kea config api to retrieve the configurations from another server. API Path: /dhcp4/config API Code: 002 API Function Name: fast_dhcp.endpoints.get_kea_config Passes only if 1. Length of returned is greater than 0. 2. FAST Type Response statusCode is 9000021000 3. FAST Type Response statusValue is 'Command execution successful' 4. Response status code is 200 """ LOGGER.info('Testing get_kea_config()') response = self.app.get('/dhcp4/config', follow_redirects=True) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) self.assertEqual(response.status_code, 200) self.assertEqual(api_response_json['statusCode'], '9000021000') self.assertEqual(api_response_json['statusValue'], "Command execution successful") self.assertNotEqual(len(api_response_json['data']['keaConfig']), 0) def test_03_add_subnet(self): """ Testing add subnet api. API Path: /dhcp4/subnets/add API Code: 007 API Function Name: fast_dhcp.endpoints.add_subnet Case: Happy Path JSON Request contains subnet_list Passes only if 1. FAST Type Response statusCode is 9000071000 2. FAST Type Response statusValue is 'Command execution successful' 3. Number of subnets should increase """ LOGGER.info('Positive Testing add_subnet()') json_req = { "subnet_list": [ { "id": config_pt['subnet_id'], "subnet": config_pt['subnet'], "pools": config_pt['pools'], "option-data": config_pt['option_data'], "reservations": [ { "hw-address": config_pt['macs'][0], "ip-address": config_pt['ips'][0], "option-data": config_pt['option_data'] }, { "hw-address": config_pt['macs'][1], "ip-address": config_pt['ips'][1] } ] } ] } before_add_subnets = get_num_subnets() LOGGER.info('Subnets before the Add API call: %d', before_add_subnets) response = self.app.post('/dhcp4/subnets/add', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) after_add_subnet = get_num_subnets() LOGGER.info('Subnets after the Add API call: %d', after_add_subnet) self.assertEqual(api_response_json['statusCode'], '9000071000') self.assertEqual(api_response_json['statusValue'], 'Command execution successful') self.assertGreater(after_add_subnet, before_add_subnets) def test_04_add_reservations(self): """ Testing the add a new reservation api to a subnet. API Path: /dhcp4/reservations/add API Code: 005 API Function Name: fast_dhcp.endpoints.add_reservations Case: Happy Path JSON Request contains subnet_id reservation info Passes only if 1. Response status code is 200 2. FAST Type Response statusCode is 9000051000 3. FAST Type Response statusValue is 'Command execution successful' 4. Length of reservation should increase after the API call """ LOGGER.info('Positive Testing add_reservations()') json_req = { "subnet_id": config_pt['subnet_id'], "reservations": [{ "hostname": "test_reservation", "hw-address": config_pt['macs'][2], "ip-address": config_pt['ips'][2], "next-server": "172.28.12.191", "server-hostname": "test_reservation_server" }] } num_reservations_before_add = get_num_reservations(self.app) LOGGER.info('Reservations after the Add API call: %d', num_reservations_before_add) response = self.app.post('/dhcp4/reservations/add', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) num_reservations_after_add = get_num_reservations(self.app) LOGGER.info('Reservations after the Add API call: %d', num_reservations_after_add) LOGGER.info('API Test Response -> %s', str(api_response_json)) self.assertEqual(response.status_code, 200) self.assertEqual(api_response_json['statusCode'], '9000051000') self.assertEqual(api_response_json['statusValue'], 'Command execution successful') self.assertGreater(num_reservations_after_add, num_reservations_before_add) def test_05_get_all_reservations(self): """ Testing the get all reservations api to retrieve the configurations from another server. API Path: /dhcp4/reservations API Code: 004 API Function Name: fast_dhcp.endpoints.get_all_reservations Case: Happy Path JSON Request contains command subnet_id Passes only if 1. Response status code is 200 2. FAST Type Response statusCode is 9000041000 3. FAST Type Response statusValue is 'Command execution successful 4. Length of reservation should be greater than 0 """ LOGGER.info('Positive Testing get_all_reservations()') json_req = { "command": "subnets", "subnet_id": config_pt['subnet_id'] } response = self.app.post('/dhcp4/reservations', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) self.assertEqual(response.status_code, 200) self.assertEqual(api_response_json['statusCode'], '9000041000') self.assertEqual(api_response_json['statusValue'], 'Command execution successful') self.assertGreater(len(api_response_json['data']['reservations']), 0) def test_06_get_ip_from_mac(self): """ Testing the fetch the IP address for mentioned MAC and Subnet ID API Path: /dhcp4/getipfrommac API Code: 003 API Function Name: fast_dhcp.endpoints.get_ip_from_mac Case: Happy Path JSON Request contains mac_address subnet_id Passes only if 1. Response status code is 200 """ LOGGER.info('Positive Testing get_ip_from_mac()') json_req = { "subnet_id": config_pt['subnet_id'], 'mac_address': 'ec:b0:e1:4c:ab:90' } response = self.app.post('/dhcp4/getipfrommac', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) self.assertEqual(response.status_code, 200) # check ip here def test_07_add_option_subnet(self): """ Testing add subnet option api. API Path: /dhcp4/subnets/options/add API Code: 009 API Function Name: fast_dhcp.endpoints.add_option_subnet Case: Happy Path JSON Request contains subnet_id options_list Passes only if 1. FAST Type Response statusCode is 9000091000 2. Number of subnets options for the id should increase. 3. FAST Type Response statusValue is 'Command execution successful """ LOGGER.info('Positive Testing add_option_subnet()') json_req = { "subnet_id": config_pt['subnet_id'], "options_list": config_pt['option_data'] } num_option_before_add_opt = get_len_subnet_options_by_id() LOGGER.info('Subnets after the Add Options API call: %d', num_option_before_add_opt) response = self.app.post('/dhcp4/subnets/options/add', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) num_option_after_add_opt = get_len_subnet_options_by_id() LOGGER.info('Subnets after the Add Options API call: %d', num_option_after_add_opt) LOGGER.info('API Test Response -> %s', str(api_response_json)) self.assertEqual(api_response_json['statusCode'], '9000091000') self.assertEqual(api_response_json['statusValue'], 'Command execution successful') self.assertGreater(num_option_after_add_opt, num_option_before_add_opt) def test_08_add_reserv_option_subnet(self): """ Testing add subnet id reservations option api. API Path: /dhcp4/subnets/reservation/options/add API Code: 011 API Function Name: fast_dhcp.endpoints.add_reserv_option_subnet Case: Happy Path JSON Request contains subnet_id mac_address options_list Passes only if 1. FAST Type Response statusCode is 9000111000 2. Number of subnets reservations options for the id and mac address should increase 3. FAST Type Response statusValue is 'Command execution successful """ mac = config_pt['macs'][2] LOGGER.info('Positive Testing add_reserv_option_subnet()') num_reserve_option_before_add_opt = \ get_len_subnet_reserv_options_by_id_and_mac(mac) LOGGER.info('Subnets before the add reserv Options API call: %d', num_reserve_option_before_add_opt) json_req = { "subnet_id": config_pt['subnet_id'], "mac": mac, "options_list": config_pt['option_data'] } response = self.app.post('/dhcp4/subnets/reservation/options/add', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) num_reserve_option_after_add_opt = \ get_len_subnet_reserv_options_by_id_and_mac(mac) LOGGER.info('Subnets after the add reserv Options API call: %d', num_reserve_option_after_add_opt) self.assertEqual(api_response_json['statusCode'], '9000111000') self.assertEqual(api_response_json['statusValue'], 'Command execution successful') self.assertGreater(num_reserve_option_after_add_opt, num_reserve_option_before_add_opt) def test_09_delete_reserv_option_subnet(self): """ Testing remove subnet id option api based on codes. API Path: /dhcp4/subnets/reservation/options/delete API Code: 012 API Function Name: fast_dhcp.endpoints.delete_reserv_option_subnet Case: Happy Path JSON Request contains subnet_id mac_address options_list Passes only if 1. FAST Type Response statusCode is 9000121000 2. Number of subnets reservations options for the id and mac address should decrease 3. FAST Type Response statusValue is 'Command execution successful """ mac = config_pt['macs'][2] LOGGER.info('Positive Testing delete_reserv_option_subnet()') num_reserve_option_before_rm_opt = \ get_len_subnet_reserv_options_by_id_and_mac(mac) LOGGER.info('Subnets before the remove reserv Options API call: %d', num_reserve_option_before_rm_opt) json_req = { "subnet_id": config_pt['subnet_id'], "mac": mac, "codes": [ config_pt['option_data'][0]["code"] ] } response = self.app.post('/dhcp4/subnets/reservation/options/delete', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) num_reserve_option_after_rm_opt = \ get_len_subnet_reserv_options_by_id_and_mac(mac) LOGGER.info('Subnets after the remove reserv Options API call: %d', num_reserve_option_after_rm_opt) self.assertEqual(api_response_json['statusCode'], '9000121000') self.assertGreater(num_reserve_option_before_rm_opt, num_reserve_option_after_rm_opt) self.assertEqual(api_response_json['statusValue'], 'Command execution successful') def test_10_delete_option_subnet(self): """ Testing remove subnet id option api based on codes. API Path: /dhcp4/subnets/delete/options API Code: 010 API Function Name: fast_dhcp.endpoints.delete_option_subnet Case: Happy Path JSON Request contains subnet_id codes Passes only if 1. FAST Type Response statusCode is 9000101000 2. Number of subnets options for the id should decrease 3. FAST Type Response statusValue is 'Command execution successful """ LOGGER.info('Positive Testing delete_option_subnet()') num_option_before_rm_opt = \ get_len_subnet_options_by_id() LOGGER.info('Subnets before the remove Options API call: %d', num_option_before_rm_opt) json_req = { "subnet_id": config_pt['subnet_id'], "codes": [ config_pt['option_data'][0]["code"] ] } response = self.app.post('/dhcp4/subnets/options/delete', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) num_option_after_rm_opt = get_len_subnet_options_by_id() LOGGER.info('Subnets after the Add Options API call: %d', num_option_after_rm_opt) self.assertEqual(api_response_json['statusCode'], '9000101000') self.assertGreater(num_option_before_rm_opt, num_option_after_rm_opt) self.assertEqual(api_response_json['statusValue'], 'Command execution successful') def test_11_remove_reservation(self): """ Testing remove reservation api to a subnet. API Path: /dhcp4/reservations/delete API Code: 006 API Function Name: fast_dhcp.endpoints.remove_reservation Case: Happy Path JSON Request contains subnet_id hw_addresses Passes only if 1. Response status code is 200 2. FAST Type Response statusCode is 9000101000 3. Number of reservations for the id should decrease 4. FAST Type Response statusValue is 'Command execution successful """ LOGGER.info('Positive Testing remove_reservation()') json_req = { "subnet_id": config_pt['subnet_id'], "hw_addresses": [config_pt['macs'][2]], } num_reservations_before_rm = get_num_reservations(self.app) response = self.app.post('/dhcp4/reservations/delete', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) self.assertEqual(response.status_code, 200) self.assertGreater(num_reservations_before_rm, get_num_reservations(self.app)) self.assertEqual(api_response_json['statusCode'], '9000061000') self.assertEqual(api_response_json['statusValue'], 'Command execution successful') def test_12_remove_subnet(self): """ Testing remove subnet api. API Path: /dhcp4/subnets/delete API Code: 008 API Function Name: fast_dhcp.endpoints.remove_subnet Case: Happy Path JSON Request contains subnet_id Passes only if 1. FAST Type Response statusCode is 9000081000 2. Number of subnets decrease 3. Response status code is 200 4. FAST Type Response statusValue is 'Command execution successful """ LOGGER.info('Positive Testing remove_subnet()') json_req = { "subnet_ids": [config_pt['subnet_id']] } before_rm_subnets = get_num_subnets() LOGGER.info('Subnets before the Remove API call: %d', before_rm_subnets) response = self.app.post('/dhcp4/subnets/delete', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) after_rm_subnet = get_num_subnets() LOGGER.info('Subnets after the Remove API call: %d', after_rm_subnet) LOGGER.info('API Test Response -> %s', json.dumps(api_response_json)) self.assertEqual(response.status_code, 200) self.assertEqual(api_response_json['statusCode'], '9000081000') self.assertGreater(before_rm_subnets, after_rm_subnet) self.assertEqual(api_response_json['statusValue'], 'Command execution successful') class NegativeTests(unittest.TestCase): """ Test Cases - Negative """ def setUp(self): """ Creating the test client using the create app from init """ test_app = create_app() self.app = test_app.test_client() LOGGER.info('Adding subnet for negative testing purpose') json_req = { "subnet_list": [ { "id": config_nt['subnet_id']['existing'], "subnet": config_nt['subnet']['existing'], "pools": config_nt['pools']['existing'], "option-data": config_nt['option_data']['valid'], "reservations": [ { "hw-address": config_nt['mac']['existing'], "ip-address": config_nt['ip']['existing'], "option-data": config_nt['option_data']['valid'] } ] } ] } response = self.app.post('/dhcp4/subnets/add', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Response -> %s', str(api_response_json)) def tearDown(self): LOGGER.info('Removing subnet after negative testing') json_req = { "subnet_ids": [config_nt['subnet_id']['existing']] } response = self.app.post('/dhcp4/subnets/delete', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', json.dumps(api_response_json)) def test_4001_get_ip_from_mac(self): """ Testing the no json case for fetch the IP address for mentioned MAC and Subnet ID API Path: /dhcp4/getipfrommac API Code: 003 API Function Name: fast_dhcp.endpoints.get_ip_from_mac JSON Request contains mac_address subnet_id Case: No JSON Request Sending empty string as request object instead of JSON Passes only if 1. FAST Type Response statusCode is 9000034001 2. FAST Type Response statusValue is Could not find JSON key """ LOGGER.info('Negative Testing get_ip_from_mac() - No JSON') json_req = "" response = self.app.post('/dhcp4/getipfrommac', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) self.assertEqual(api_response_json['statusCode'], '9000034001') self.assertEqual(api_response_json['statusValue'], ERROR_4001_VALUE) def test_4001_get_all_reservations(self): """ Testing the no json case for get all reservations api to retrieve the configurations from kea server. API Path: /dhcp4/reservations API Code: 004 API Function Name: fast_dhcp.endpoints.get_all_reservations JSON Request contains command subnet_id Case: No json data Sending an empty json as a empty string Passes only if 1. FAST Type Response statusCode is 9000044001 2. FAST Type Response statusValue is Could not find JSON key """ LOGGER.info('Negative Testing get_all_reservations() - NO JSON') json_req = "" response = self.app.post('/dhcp4/reservations', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) self.assertEqual(api_response_json['statusCode'], '9000044001') self.assertEqual(api_response_json['statusValue'], ERROR_4001_VALUE) def test_4001_add_reservations(self): """ Testing the empty json scenario for add a new reservation api to a subnet. API Path: /dhcp4/reservations/add API Code: 005 API Function Name: fast_dhcp.endpoints.add_reservations JSON Request contains subnet_id reservation info Case: No json data Sending an empty string instead of json Passes only if 1. FAST Type Response statusCode is 9000054001 2. FAST Type Response statusValue is Could not find JSON key 3. Length of reservation does not change after the API call """ LOGGER.info('Negative Testing add_reservations() - NO JSON') json_req = "" num_reservations_before_add = get_num_reservations(self.app) LOGGER.info('Reservations before add_reservations() -> %s', str(num_reservations_before_add)) response = self.app.post('/dhcp4/reservations/add', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) num_reservations_after_add = get_num_reservations(self.app) LOGGER.info('Reservations after add_reservations() -> %s', str(num_reservations_after_add)) self.assertEqual(api_response_json['statusCode'], '9000054001') self.assertEqual(api_response_json['statusValue'], ERROR_4001_VALUE) self.assertEqual(num_reservations_after_add, num_reservations_before_add) def test_4001_remove_reservation(self): """ Testing negative case of no json for remove reservation api to a subnet. API Path: /dhcp4/reservations/delete API Code: 006 API Function Name: fast_dhcp.endpoints.remove_reservation JSON Request contains subnet_id hw_addresses Case: No json data Sending an empty string instead of json Passes only if 1. FAST Type Response statusCode is 9000064001 2. FAST Type Response statusValue is Could not find JSON key 3. Length of reservation should not change """ LOGGER.info('Negative Testing remove_reservation() - No JSON') json_req = "" num_reservations_before_rm = get_num_reservations(self.app) LOGGER.info('Reservations before remove_reservations() -> %s', str(num_reservations_before_rm)) response = self.app.post('/dhcp4/reservations/delete', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) num_reservations_after_rm = get_num_reservations(self.app) LOGGER.info('Reservations after remove_reservations() -> %s', str(num_reservations_after_rm)) self.assertEqual(api_response_json['statusCode'], '9000064001') self.assertEqual(api_response_json['statusValue'], ERROR_4001_VALUE) self.assertEqual(num_reservations_before_rm, num_reservations_after_rm) def test_4001_add_subnet(self): """ Testing NO JSON scenario for add subnet api. API Path: /dhcp4/subnets/add API Code: 007 API Function Name: fast_dhcp.endpoints.add_subnet JSON Request contains subnet_list Case: No json data Sending an empty string instead of json Passes only if 1. FAST Type Response statusCode is 9000074001 2. FAST Type Response statusValue is Could not find JSON key 3. Number of subnets should not change """ before_add_subnets = get_num_subnets() LOGGER.info('Subnets before the Add API call: %d', before_add_subnets) LOGGER.info('Negative Testing add_subnet() - No JSON') json_req = "" response = self.app.post('/dhcp4/subnets/add', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) after_add_subnet = get_num_subnets() LOGGER.info('Subnets after the Add API call: %d', after_add_subnet) self.assertEqual(api_response_json['statusCode'], '9000074001') self.assertEqual(api_response_json['statusValue'], ERROR_4001_VALUE) self.assertEqual(before_add_subnets, after_add_subnet) def test_4001_remove_subnet(self): """ Testing no json scenario for remove subnet api. API Path: /dhcp4/subnets/delete API Code: 008 API Function Name: fast_dhcp.endpoints.remove_subnet JSON Request contains subnet_id Case: No json data Sending an empty string instead of json Passes only if 1. FAST Type Response statusCode is 9000084001 2. FAST Type Response statusValue is Could not find JSON key 3. Number of subnets should not change """ LOGGER.info('Negative Testing remove_subnet() - No JSON') json_req = "" before_rm_subnets = get_num_subnets() LOGGER.info('Subnets before the Remove API call: %d', before_rm_subnets) response = self.app.post('/dhcp4/subnets/delete', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) after_rm_subnet = get_num_subnets() LOGGER.info('Subnets after the Remove API call: %d', after_rm_subnet) LOGGER.info('API Test Response -> %s', str(api_response_json)) self.assertEqual(api_response_json['statusCode'], '9000084001') self.assertEqual(api_response_json['statusValue'], ERROR_4001_VALUE) self.assertEqual(before_rm_subnets, after_rm_subnet) def test_4001_add_option_subnet(self): """ Testing no json scenario for add subnet option api. API Path: /dhcp4/subnets/options/add API Code: 009 API Function Name: fast_dhcp.endpoints.add_option_subnet JSON Request contains subnet_id options_list Case: No json data Sending an empty string instead of json Passes only if 1. FAST Type Response statusCode is 9000094001 2. FAST Type Response statusValue is Could not find JSON key 3. Number of subnets options for the id should NOT change """ LOGGER.info('Negative Testing add_option_subnet() - No JSON') json_req = "" num_option_before_add_opt = get_len_subnet_options_by_id() LOGGER.info('Subnets before the Add Options API call: %d', num_option_before_add_opt) response = self.app.post('/dhcp4/subnets/options/add', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) num_option_after_add_opt = get_len_subnet_options_by_id() LOGGER.info('Subnets after the Add Options API call: %d', num_option_after_add_opt) LOGGER.info('API Test Response -> %s', str(api_response_json)) self.assertEqual(api_response_json['statusCode'], '9000094001') self.assertEqual(api_response_json['statusValue'], ERROR_4001_VALUE) self.assertEqual(num_option_before_add_opt, num_option_after_add_opt) def test_4001_delete_option_subnet(self): """ Testing no json scenario for remove subnet id option api based on codes. API Path: /dhcp4/subnets/options/delete API Code: 010 API Function Name: fast_dhcp.endpoints.delete_option_subnet Case: No JSON JSON Request contains subnet_id codes Case: No json data Sending an empty string instead of json Passes only if 1. FAST Type Response statusCode is 9000104001 2. FAST Type Response statusValue is Could not find JSON key 3. Number of subnets options for the id should NOT change """ LOGGER.info('Negative Testing delete_option_subnet() - No JSON') num_option_before_rm_opt = get_len_subnet_options_by_id() LOGGER.info('Subnets before the remove Options API call: %d', num_option_before_rm_opt) json_req = "" response = self.app.post('/dhcp4/subnets/options/delete', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) num_option_after_rm_opt = get_len_subnet_options_by_id() LOGGER.info('Subnets after the Add Options API call: %d', num_option_after_rm_opt) self.assertEqual(api_response_json['statusCode'], '9000104001') self.assertEqual(api_response_json['statusValue'], ERROR_4001_VALUE) self.assertEqual(num_option_before_rm_opt, num_option_after_rm_opt) def test_4001_add_subnet_reservation_option(self): """ Testing no json case for add subnet id reservations option api . API Path: /dhcp4/subnets/reservation/options/add API Code: 011 API Function Name: fast_dhcp.endpoints.add_reserv_option_subnet JSON Request contains subnet_id mac_address options_list Case: No json data Sending an empty string instead of json Passes only if 1. FAST Type Response statusCode is 9000111000 2. FAST Type Response statusValue is Could not find JSON key 3. Number of subnets reservations options for the id and mac address should not change """ LOGGER.info('Negative Testing add_reserv_option_subnet() - No JSON') num_reserve_option_before_add_opt = \ get_len_subnet_reserv_options_by_id_and_mac() LOGGER.info('Subnets before the add reserv Options API call: %s', str(num_reserve_option_before_add_opt)) json_req = "" response = self.app.post('/dhcp4/subnets/reservation/options/add', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) num_reserve_option_after_add_opt = \ get_len_subnet_reserv_options_by_id_and_mac() LOGGER.info('Subnets after the add reserv Options API call: %s', str(num_reserve_option_after_add_opt)) self.assertEqual(api_response_json['statusCode'], '9000114001') self.assertEqual(api_response_json['statusValue'], ERROR_4001_VALUE) self.assertEqual(num_reserve_option_after_add_opt, num_reserve_option_before_add_opt) def test_4001_delete_subnet_reservation_option(self): """ Testing no json case for remove subnet id option api based on codes. API Path: /dhcp4/subnets/reservation/options//delete API Code: 012 API Function Name: fast_dhcp.endpoints.delete_reserv_option_subnet JSON Request contains subnet_id mac_address options_list Case: No json data Sending an empty string instead of json Passes only if 1. FAST Type Response statusCode is 9000121000 2. Number of subnets reservations options for the id and mac address should decrease """ LOGGER.info('Negative Testing delete_reserv_option_subnet() - No JSON') num_reserve_option_before_rm_opt = \ get_len_subnet_reserv_options_by_id_and_mac() LOGGER.info('Subnets before the remove reserv Options API call: %d', num_reserve_option_before_rm_opt) json_req = "" response = self.app.post('/dhcp4/subnets/reservation/options/delete', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) num_reserve_option_after_rm_opt = \ get_len_subnet_reserv_options_by_id_and_mac() LOGGER.info('Subnets after the remove reserv Options API call: %d', num_reserve_option_after_rm_opt) self.assertEqual(api_response_json['statusCode'], '9000124001') self.assertEqual(api_response_json['statusValue'], ERROR_4001_VALUE) self.assertEqual(num_reserve_option_before_rm_opt, num_reserve_option_after_rm_opt) def test_4003_get_ip_from_mac_incorrect_subnet_id(self): """ Testing the fetch the IP address for mentioned MAC and Subnet ID API Path: /dhcp4/getipfrommac API Code: 003 API Function Name: fast_dhcp.endpoints.get_ip_from_mac JSON Request contains mac_address subnet_id Case: Incorrect Subnet_id Sending a subnet id which does not exist on the dhcp4 Passes only if 1. FAST Type Response statusCode is 9000034003 2. FAST Type Response statusValue is "IP Address not found" """ LOGGER.info('Negative Testing get_ip_from_mac() - Incorrect subnet id') json_req = { "subnet_id": config_nt['subnet_id']['incorrect'], "mac_address": [ config_nt["mac"]['existing'] ] } response = self.app.post('/dhcp4/getipfrommac', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) self.assertEqual(api_response_json['statusCode'], '9000034003') self.assertEqual(api_response_json['statusValue'], ERROR_4003_VALUE) def test_4003_get_ip_from_mac_incorrect_mac_address(self): """ Testing the fetch the IP address for mentioned MAC and Subnet ID API Path: /dhcp4/getipfrommac API Code: 003 API Function Name: fast_dhcp.endpoints.get_ip_from_mac JSON Request contains mac_address subnet_id Case: Incorrect mac_address Sending a mac_address which does not exist on the subnet Passes only if 1. FAST Type Response statusCode is 9000034003 2. FAST Type Response statusValue is "IP Address not found" """ LOGGER.info('Negative Testing get_ip_from_mac() - ' 'incorrect hw_address / mac address') json_req = { "subnet_id": config_nt['subnet_id']['existing'], "mac_address": [ config_nt["mac"]['incorrect'] ] } response = self.app.post('/dhcp4/getipfrommac', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) self.assertEqual(api_response_json['statusCode'], '9000034003') self.assertEqual(api_response_json['statusValue'], ERROR_4003_VALUE) def test_4005_get_all_reservations_incorrect_subnet_id(self): """ Testing the get all reservation api to retrieve the configurations from kea server. API Path: /dhcp4/reservations API Code: 004 API Function Name: fast_dhcp.endpoints.get_all_reservations JSON Request: command subnet_id Case: Incorrect subnet id sending a subnet id which will not exist in the dhcp4 Passes only if 1. FAST Type Response statusCode is 9000044005 2. FAST Type Response statusValue is Unable to fetch reservations from server. 3. FAST Type Response data will have error as Unable to find the subnet with id {} from config obtained from server at {}:{} """ LOGGER.info('Negative Testing get_all_reservations() - Incorrect Subnet ID') json_req = { "subnet_id": config_nt['subnet_id']['incorrect'] } response = self.app.post('/dhcp4/reservations', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) self.assertEqual(api_response_json['statusCode'], '9000044005') self.assertEqual(api_response_json['statusValue'], ERROR_4005_VALUE) self.assertEqual(api_response_json["data"]["error"], SUBNET_NOT_FOUND.format(config_nt['subnet_id']['incorrect'], DHCP_IP, DHCP_PORT)) def test_4006_add_reservations_incorrect_subnet_id(self): """ Testing the add a new reservation api to a subnet. API Path: /dhcp4/reservations/add API Code: 005 API Function Name: fast_dhcp.endpoints.add_reservations JSON Request contains subnet_id reservation info Case: Incorrect Subnet ID sending a subnet id which will not exist in the dhcp4 Passes only if 1. FAST Type Response statusCode is 9000054006 2. FAST Type Response statusValue is "Failed to add reservation due to an issue with KEA server" 3. FAST Type Response data will have error as Unable to find the subnet with id {} from config obtained from server at {}:{} """ LOGGER.info('Negative Testing add_reservations() - incorrect subnet_id') json_req = { "subnet_id": config_nt['subnet_id']['incorrect'], "reservations": [ { "hostname": "test_reservation", "hw-address": config_nt['mac']['valid'], "ip-address": config_nt['ip']['valid'], "next-server": "172.28.12.191", "server-hostname": "test_reservation_server" } ] } response = self.app.post('/dhcp4/reservations/add', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) self.assertEqual(api_response_json["statusCode"], "9000054006") self.assertEqual(api_response_json["statusValue"], ERROR_4006_VALUE) self.assertEqual(api_response_json["data"]["error"], SUBNET_NOT_FOUND.format(config_nt['subnet_id']['incorrect'], DHCP_IP, DHCP_PORT)) def test_4007_add_reservations_duplicate_ip_address(self): """ Testing the add a new reservation api to a subnet. API Path: /dhcp4/reservations/add API Code: 005 API Function Name: fast_dhcp.endpoints.add_reservations JSON Request contains subnet_id reservation info Case: Duplicate IP Address Sending an existing reserved IP added during setup in the subnet. Passes only if 1. FAST Type Response statusCode is 9000054007 2. FAST Type Response statusValue is Failed to add reservation 3. Length of reservation should not have changed """ LOGGER.info('Negative Testing add_reservations() - Existing IP address') json_req = { "subnet_id": config_nt['subnet_id']['existing'], "reservations": [ { "hostname": "test_reservation", "hw-address": config_nt['mac']['valid'], "ip-address": config_nt['ip']['existing'], "next-server": "172.28.12.191", "server-hostname": "test_reservation_server" } ] } num_reservations_before_add = get_num_reservations(self.app) response = self.app.post('/dhcp4/reservations/add', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) num_reservations_after_add = get_num_reservations(self.app) self.assertEqual(api_response_json["statusCode"], "9000054007") self.assertEqual(api_response_json["statusValue"], ERROR_4007_VALUE) self.assertEqual(num_reservations_after_add, num_reservations_before_add) def test_4007_add_reservations_duplicate_mac_address(self): """ Testing the add a new reservation api to a subnet. API Path: /dhcp4/reservations/add API Code: 005 API Function Name: fast_dhcp.endpoints.add_reservations JSON Request contains subnet_id reservation info Case: Duplicate Hardware Address Sending an existing reserved mac added during setup in the subnet. Passes only if 1. FAST Type Response statusCode is 9000054007 2. FAST Type Response statusValue is Failed to add reservation 3. Length of reservation should not have changed """ LOGGER.info('Negative Testing add_reservations() - Existing MAC address') json_req = { "subnet_id": config_nt['subnet_id']['existing'], "reservations": [ { "hostname": "test_reservation", "hw-address": config_nt['mac']['existing'], "ip-address": config_nt['ip']['valid'], "next-server": "172.28.12.191", "server-hostname": "test_reservation_server" } ] } num_reservations_before_add = get_num_reservations(self.app) response = self.app.post('/dhcp4/reservations/add', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) num_reservations_after_add = get_num_reservations(self.app) self.assertEqual(api_response_json["statusCode"], "9000054007") self.assertEqual(api_response_json["statusValue"], ERROR_4007_VALUE) self.assertEqual(num_reservations_after_add, num_reservations_before_add) def test_4007_add_reservations_incorrect_mac_address(self): """ Testing the add a new reservation api to a subnet. API Path: /dhcp4/reservations/add API Code: 005 API Function Name: fast_dhcp.endpoints.add_reservations JSON Request contains subnet_id reservation info Case: Incorrect MAC Address Sending a mac address which is not in correct format. Passes only if 1. FAST Type Response statusCode is 9000054007 2. FAST Type Response statusValue is Failed to add reservation 3. Length of reservation should not have changed """ LOGGER.info('Negative Testing add_reservations() - Invalid MAC address') json_req = { "subnet_id": config_nt['subnet_id']['existing'], "reservations": [ { "hostname": "test_reservation", "hw-address": config_nt['mac']['incorrect'], "ip-address": config_nt['ip']['valid'], "next-server": "172.28.12.191", "server-hostname": "test_reservation_server" } ] } num_reservations_before_add = get_num_reservations(self.app) response = self.app.post('/dhcp4/reservations/add', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) num_reservations_after_add = get_num_reservations(self.app) self.assertEqual(api_response_json["statusCode"], "9000054007") self.assertEqual(api_response_json["statusValue"], ERROR_4007_VALUE) self.assertEqual(num_reservations_after_add, num_reservations_before_add) def test_4007_add_reservations_incorrect_option_code(self): """ Testing the add a new reservation api to a subnet. API Path: /dhcp4/reservations/add API Code: 005 API Function Name: fast_dhcp.endpoints.add_reservations JSON Request contains subnet_id reservation info Case: Incorrect Option Code Sending a code outside of DHCP codes Passes only if 1. FAST Type Response statusCode is 9000054007 2. FAST Type Response statusValue is Failed to add reservation 3. Length of reservation should not have changed """ LOGGER.info('Negative Testing add_reservations() - Incorrect option code') json_req = { "subnet_id": config_nt['subnet_id']['existing'], "reservations": [ { "hostname": "test_reservation", "hw-address": config_nt['mac']['valid'], "ip-address": config_nt['ip']['valid'], "next-server": "172.28.12.191", "server-hostname": "test_reservation_server", "option-data": config_nt['option_data']['incorrect'] } ] } num_reservations_before_add = get_num_reservations(self.app) response = self.app.post('/dhcp4/reservations/add', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) num_reservations_after_add = get_num_reservations(self.app) self.assertEqual(api_response_json["statusCode"], "9000054007") self.assertEqual(api_response_json["statusValue"], ERROR_4007_VALUE) self.assertEqual(num_reservations_after_add, num_reservations_before_add) def test_4008_remove_reservation_incorrect_subnet_id(self): """ Testing remove reservation api to a subnet. API Path: /dhcp4/reservations/delete API Code: 006 API Function Name: fast_dhcp.endpoints.remove_reservation JSON Request contains subnet_id hw_addresses Case: Incorrect Subnet_id Sending a subnet id which does not exist on the dhcp4 Passes only if 1. FAST Type Response statusCode is 9000064008 2. FAST Type Response statusValue is "Failed to remove reservation due to an issue with KEA server" 3. FAST Type Response data will have error as Unable to find the subnet with id {} from config obtained from server at {}:{} """ LOGGER.info('Negative Testing remove_reservation() - incorrect subnet_id') json_req = { "subnet_id": config_nt['subnet_id']['incorrect'], "hw_addresses": [ config_nt['mac']['existing'] ] } response = self.app.post('/dhcp4/reservations/delete', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) self.assertEqual(api_response_json['statusCode'], '9000064008') self.assertEqual(api_response_json["statusValue"], ERROR_4008_VALUE) self.assertEqual(api_response_json["data"]["error"], SUBNET_NOT_FOUND.format(config_nt['subnet_id']['incorrect'], DHCP_IP, DHCP_PORT)) def test_4008_remove_reservation_empty_hw_address_list(self): """ Testing remove reservation api to a subnet. API Path: /dhcp4/reservations/delete API Code: 006 API Function Name: fast_dhcp.endpoints.remove_reservation JSON Request contains subnet_id hw_addresses Case: Empty Hardware Address List Sending a empty list for mac_addresses Passes only if 1. FAST Type Response statusCode is 9000064008 2. FAST Type Response statusValue is "Failed to remove reservation due to an issue with KEA server" 3. FAST Type Response data will have error as Specified reservation mac(s) do not exist 4. Length of reservation should not change """ LOGGER.info('Negative Testing remove_reservation() - empty hw address list') json_req = { "subnet_id": config_nt['subnet_id']['existing'], "hw_addresses": [] } num_reservations_before_rm = get_num_reservations(self.app) response = self.app.post('/dhcp4/reservations/delete', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) num_reservations_after_rm = get_num_reservations(self.app) self.assertEqual(api_response_json['statusCode'], '9000064008') self.assertEqual(api_response_json["statusValue"], ERROR_4008_VALUE) self.assertEqual(num_reservations_before_rm, num_reservations_after_rm) self.assertEqual(api_response_json["data"]["error"], RESERVATION_NOT_FOUND) def test_4008_remove_reservation_incorrect_hw_address(self): """ Testing remove reservation api to a subnet. API Path: /dhcp4/reservations/delete API Code: 006 API Function Name: fast_dhcp.endpoints.remove_reservation JSON Request contains subnet_id hw_addresses Case: Incorrect MAC Address Sending a mac address which is not present in the config. Passes only if 1. FAST Type Response statusCode is 9000064008 2. FAST Type Response statusValue is "Failed to remove reservation due to an issue with KEA server" 3. FAST Type Response data will have error as 'Specified reservation mac(s) do not exist' 4. Length of reservation should not change """ LOGGER.info('Negative Testing remove_reservation() - ' 'incorrect hw address') json_req = { "subnet_id": config_nt['subnet_id']['existing'], "hw_addresses": [ config_nt['mac']['valid'] ] } num_reservations_before_rm = get_num_reservations(self.app) response = self.app.post('/dhcp4/reservations/delete', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) num_reservations_after_rm = get_num_reservations(self.app) self.assertEqual(api_response_json['statusCode'], '9000064008') self.assertEqual(api_response_json["statusValue"], ERROR_4008_VALUE) self.assertEqual(num_reservations_before_rm, num_reservations_after_rm) self.assertEqual(api_response_json["data"]["error"], RESERVATION_NOT_FOUND) def test_4008_remove_reservation_invalid_hw_address(self): """ Testing remove reservation api to a subnet. API Path: /dhcp4/reservations/delete API Code: 006 API Function Name: fast_dhcp.endpoints.remove_reservation JSON Request contains subnet_id hw_addresses Case: Invalid MAC Address Sending a mac address which is not in correct format. Passes only if 1. FAST Type Response statusCode is 9000064008 2. FAST Type Response statusValue is "Failed to remove reservation due to an issue with KEA server" 3. FAST Type Response data will have error as 'Specified reservation mac(s) do not exist' 4. Length of reservation should not change """ LOGGER.info('Negative Testing remove_reservation() - ' 'invalid hw address') json_req = { "subnet_id": config_nt['subnet_id']['existing'], "hw_addresses": [ config_nt['mac']['incorrect'] ] } num_reservations_before_rm = get_num_reservations(self.app) response = self.app.post('/dhcp4/reservations/delete', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) num_reservations_after_rm = get_num_reservations(self.app) self.assertEqual(api_response_json['statusCode'], '9000064008') self.assertEqual(api_response_json["statusValue"], ERROR_4008_VALUE) self.assertEqual(num_reservations_before_rm, num_reservations_after_rm) self.assertEqual(api_response_json["data"]["error"], RESERVATION_NOT_FOUND) def test_4011_add_subnet_duplicate_subnet_id(self): """ Testing add subnet api. API Path: /dhcp4/subnets/add API Code: 007 API Function Name: fast_dhcp.endpoints.add_subnet JSON Request contains subnet_list Case: Duplicate Subnet ID Sending an ID which is already been used. Passes only if 1. FAST Type Response statusCode is 9000074011 2. FAST Type Response statusValue is 'Failed to add subnet' 3. Number of subnets should not change """ LOGGER.info('Negative Testing add_subnet() - Duplicate subnet id') json_req = { "subnet_list": [ { "id": config_nt['subnet_id']['existing'], "subnet": config_nt['subnet']['valid'], "pools": config_nt['pools']['valid'], "option-data": config_nt['option_data']['valid'], "reservations": [ { "hw-address": config_nt['mac']['valid'], "ip-address": config_nt['ip']['valid'] } ] } ] } before_add_subnets = get_num_subnets() LOGGER.info('Subnets before the Add API call: %d', before_add_subnets) response = self.app.post('/dhcp4/subnets/add', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) after_add_subnet = get_num_subnets() LOGGER.info('Subnets after the Add API call: %d', after_add_subnet) self.assertEqual(api_response_json['statusCode'], '9000074011') self.assertEqual(api_response_json['statusValue'], ERROR_4011_VALUE) self.assertEqual(before_add_subnets, after_add_subnet) def test_4011_add_subnet_duplicate_subnet(self): """ Testing add subnet api. API Path: /dhcp4/subnets/add API Code: 007 API Function Name: fast_dhcp.endpoints.add_subnet JSON Request contains subnet_list Case: Duplicate Subnet Sending a subnet which is already been used. Passes only if 1. FAST Type Response statusCode is 9000074011 2. FAST Type Response statusValue is 'Failed to add subnet' 3. Number of subnets should not change """ LOGGER.info('Negative Testing add_subnet() - Duplicate subnet') json_req = { "subnet_list": [ { "id": config_nt['subnet_id']['valid'], "subnet": config_nt['subnet']['existing'], "pools": config_nt['pools']['valid'], "option-data": config_nt['option_data']['valid'], "reservations": [ { "hw-address": config_nt['mac']['valid'], "ip-address": config_nt['ip']['valid'] } ] } ] } before_add_subnets = get_num_subnets() LOGGER.info('Subnets before the Add API call: %d', before_add_subnets) response = self.app.post('/dhcp4/subnets/add', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) after_add_subnet = get_num_subnets() LOGGER.info('Subnets after the Add API call: %d', after_add_subnet) self.assertEqual(api_response_json['statusCode'], '9000074011') self.assertEqual(api_response_json['statusValue'], ERROR_4011_VALUE) self.assertEqual(before_add_subnets, after_add_subnet) def test_4011_add_subnet_incorrect_pool(self): """ Testing add subnet api. API Path: /dhcp4/subnets/add API Code: 007 API Function Name: fast_dhcp.endpoints.add_subnet JSON Request contains subnet_list Case: Incorrect Pool Sending a pool which is outside the subnet Passes only if 1. FAST Type Response statusCode is 9000074011 2. FAST Type Response statusValue is 'Failed to add subnet' 3. Number of subnets should not change """ LOGGER.info('Negative Testing add_subnet() - Incorrect Pool') json_req = { "subnet_list": [ { "id": config_nt['subnet_id']['valid'], "subnet": config_nt['subnet']['valid'], "pools": config_nt['pools']['incorrect'], "option-data": config_nt['option_data']['valid'], "reservations": [ { "hw-address": config_nt['mac']['valid'], "ip-address": config_nt['ip']['valid'] } ] } ] } before_add_subnets = get_num_subnets() LOGGER.info('Subnets before the Add API call: %d', before_add_subnets) response = self.app.post('/dhcp4/subnets/add', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) after_add_subnet = get_num_subnets() LOGGER.info('Subnets after the Add API call: %d', after_add_subnet) self.assertEqual(api_response_json['statusCode'], '9000074011') self.assertEqual(api_response_json['statusValue'], ERROR_4011_VALUE) self.assertEqual(before_add_subnets, after_add_subnet) def test_4011_add_subnet_invalid_option_code(self): """ Testing add subnet api. API Path: /dhcp4/subnets/add API Code: 007 API Function Name: fast_dhcp.endpoints.add_subnet Case: Duplicate Subnet ID Sending an option code outside of the DHCP code list. JSON Request contains subnet_list Passes only if 1. FAST Type Response statusCode is 9000074011 2. FAST Type Response statusValue is 'Failed to add subnet' 3. Number of subnets should not change """ LOGGER.info('Negative Testing add_subnet() - Incorrect Option Data') json_req = { "subnet_list": [ { "id": config_nt['subnet_id']['valid'], "subnet": config_nt['subnet']['valid'], "pools": config_nt['pools']['valid'], "option-data": config_nt['option_data']['incorrect'], "reservations": [ { "hw-address": config_nt['mac']['valid'], "ip-address": config_nt['ip']['valid'] } ] } ] } before_add_subnets = get_num_subnets() LOGGER.info('Subnets before the Add API call: %d', before_add_subnets) response = self.app.post('/dhcp4/subnets/add', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) after_add_subnet = get_num_subnets() LOGGER.info('Subnets after the Add API call: %d', after_add_subnet) self.assertEqual(api_response_json['statusCode'], '9000074011') self.assertEqual(api_response_json['statusValue'], ERROR_4011_VALUE) self.assertEqual(before_add_subnets, after_add_subnet) def test_4011_add_subnet_invalid_reservation_option_code(self): """ Testing add subnet api. API Path: /dhcp4/subnets/add API Code: 007 API Function Name: fast_dhcp.endpoints.add_subnet Case: Invalid option code in reservation Sending an option code outside of the DHCP code list for reservation. JSON Request contains subnet_list Passes only if 1. FAST Type Response statusCode is 9000074011 2. FAST Type Response statusValue is 'Failed to add subnet' 3. Number of subnets should not change """ LOGGER.info('Negative Testing add_subnet() - Incorrect Option Data') json_req = { "subnet_list": [ { "id": config_nt['subnet_id']['valid'], "subnet": config_nt['subnet']['valid'], "pools": config_nt['pools']['valid'], "option-data": config_nt['option_data']['valid'], "reservations": [ { "hw-address": config_nt['mac']['valid'], "ip-address": config_nt['ip']['valid'], "option-data": config_nt['option_data']['incorrect'], } ] } ] } before_add_subnets = get_num_subnets() LOGGER.info('Subnets before the Add API call: %d', before_add_subnets) response = self.app.post('/dhcp4/subnets/add', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) after_add_subnet = get_num_subnets() LOGGER.info('Subnets after the Add API call: %d', after_add_subnet) self.assertEqual(api_response_json['statusCode'], '9000074011') self.assertEqual(api_response_json['statusValue'], ERROR_4011_VALUE) self.assertEqual(before_add_subnets, after_add_subnet) def test_4011_add_subnet_duplicate_reservation_ip_address(self): """ Testing add subnet api. API Path: /dhcp4/subnets/add API Code: 007 API Function Name: fast_dhcp.endpoints.add_subnet JSON Request contains subnet_list Case: Duplicate reservation IP Address Sending an IP which has already been used. Passes only if 1. FAST Type Response statusCode is 9000074011 2. FAST Type Response statusValue is 'Failed to add subnet' 3. Number of subnets should not change """ LOGGER.info('Negative Testing add_subnet() - Incorrect Option Data') json_req = { "subnet_list": [ { "id": config_nt['subnet_id']['valid'], "subnet": config_nt['subnet']['valid'], "pools": config_nt['pools']['valid'], "option-data": config_nt['option_data']['valid'], "reservations": [ { "hw-address": config_nt['mac']['valid'], "ip-address": config_nt['ip']['existing'], "option-data": config_nt['option_data']['valid'] } ] } ] } before_add_subnets = get_num_subnets() LOGGER.info('Subnets before the Add API call: %d', before_add_subnets) response = self.app.post('/dhcp4/subnets/add', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) after_add_subnet = get_num_subnets() LOGGER.info('Subnets after the Add API call: %d', after_add_subnet) self.assertEqual(api_response_json['statusCode'], '9000074011') self.assertEqual(api_response_json['statusValue'], ERROR_4011_VALUE) self.assertEqual(before_add_subnets, after_add_subnet) def test_4011_add_subnet_duplicate_reservation_mac_address(self): """ Testing add subnet api. API Path: /dhcp4/subnets/add API Code: 007 API Function Name: fast_dhcp.endpoints.add_subnet JSON Request contains subnet_list Case: Duplicate reservation Mac Address Sending an MAC which has already been used. Passes only if 1. FAST Type Response statusCode is 9000074011 2. FAST Type Response statusValue is 'Failed to add subnet' 3. Number of subnets should not change """ LOGGER.info('Negative Testing add_subnet() - Incorrect Option Data') json_req = { "subnet_list": [ { "id": config_nt['subnet_id']['valid'], "subnet": config_nt['subnet']['valid'], "pools": config_nt['pools']['valid'], "option-data": config_nt['option_data']['valid'], "reservations": [ { "hw-address": config_nt['mac']['existing'], "ip-address": config_nt['ip']['valid'] } ] } ] } before_add_subnets = get_num_subnets() LOGGER.info('Subnets before the Add API call: %d', before_add_subnets) response = self.app.post('/dhcp4/subnets/add', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) after_add_subnet = get_num_subnets() LOGGER.info('Subnets after the Add API call: %d', after_add_subnet) self.assertEqual(api_response_json['statusCode'], '9000074011') self.assertEqual(api_response_json['statusValue'], ERROR_4011_VALUE) self.assertEqual(before_add_subnets, after_add_subnet) def test_4011_add_subnet_invalid_reservation_mac_address(self): """ Testing add subnet api. API Path: /dhcp4/subnets/add API Code: 007 API Function Name: fast_dhcp.endpoints.add_subnet JSON Request contains subnet_list Case: Invalic reservation Mac Address Sending an MAC which has incorrect ormat. Passes only if 1. FAST Type Response statusCode is 9000074011 2. FAST Type Response statusValue is 'Failed to add subnet' 3. Number of subnets should not change """ LOGGER.info('Negative Testing add_subnet() - Incorrect Option Data') json_req = { "subnet_list": [ { "id": config_nt['subnet_id']['valid'], "subnet": config_nt['subnet']['valid'], "pools": config_nt['pools']['valid'], "option-data": config_nt['option_data']['valid'], "reservations": [ { "hw-address": config_nt['mac']['incorrect'], "ip-address": config_nt['ip']['valid'] } ] } ] } before_add_subnets = get_num_subnets() LOGGER.info('Subnets before the Add API call: %d', before_add_subnets) response = self.app.post('/dhcp4/subnets/add', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) after_add_subnet = get_num_subnets() LOGGER.info('Subnets after the Add API call: %d', after_add_subnet) self.assertEqual(api_response_json['statusCode'], '9000074011') self.assertEqual(api_response_json['statusValue'], ERROR_4011_VALUE) self.assertEqual(before_add_subnets, after_add_subnet) def test_4012_remove_subnet_incorrect_subnet_id(self): """ Testing remove subnet api. API Path: /dhcp4/subnets/delete API Code: 008 API Function Name: fast_dhcp.endpoints.remove_subnet JSON Request contains subnet_id Case: Incorrect subnet id sending a subnet id which will not exist in the dhcp4 Passes only if 1. FAST Type Response statusCode is 9000084012 2. FAST Type Response statusValue is "Failed to remove subnet due to an issue with KEA server response" 3. FAST Type Response data has error - Specified subnet id(s) do not exist 4. Number of subnets should not change """ LOGGER.info('Negative Testing remove_subnet() - Incorrect subnet id') json_req = { "subnet_ids": [config_nt['subnet_id']['incorrect']] } before_rm_subnets = get_num_subnets() LOGGER.info('Subnets before the Remove API call: %d', before_rm_subnets) response = self.app.post('/dhcp4/subnets/delete', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) after_rm_subnet = get_num_subnets() LOGGER.info('Subnets after the Remove API call: %d', after_rm_subnet) LOGGER.info('API Test Response -> %s', str(api_response_json)) self.assertEqual(api_response_json['statusCode'], '9000084012') self.assertEqual(api_response_json['statusValue'], ERROR_4012_VALUE) self.assertEqual(api_response_json["data"]["error"], SUBNETS_NOT_FOUND) self.assertEqual(before_rm_subnets, after_rm_subnet) def test_4012_remove_subnet_empty_list(self): """ Testing remove subnet api. API Path: /dhcp4/subnets/delete API Code: 008 API Function Name: fast_dhcp.endpoints.remove_subnet JSON Request contains subnet_id Case: Empty subnet id list Sending an empty list for subnets. Passes only if 1. FAST Type Response statusCode is 9000084010 2. FAST Type Response statusValue is Specified subnet not found 3. FAST Type Response data has error as Specified subnet not found 4. Number of subnets should not change """ LOGGER.info('Negative Testing remove_subnet() - empty subnet id list') json_req = { "subnet_ids": [] } before_rm_subnets = get_num_subnets() LOGGER.info('Subnets before the Remove API call: %d', before_rm_subnets) response = self.app.post('/dhcp4/subnets/delete', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) after_rm_subnet = get_num_subnets() LOGGER.info('Subnets after the Remove API call: %d', after_rm_subnet) LOGGER.info('API Test Response -> %s', str(api_response_json)) self.assertEqual(api_response_json['statusCode'], '9000084012') self.assertEqual(api_response_json['statusValue'], ERROR_4012_VALUE) self.assertEqual(api_response_json['data']['error'], SUBNETS_NOT_FOUND) self.assertEqual(before_rm_subnets, after_rm_subnet) def test_4014_add_option_subnet_incorrect_subnet_id(self): """ Testing add subnet option api. API Path: /dhcp4/subnets/add/options API Code: 009 API Function Name: fast_dhcp.endpoints.add_option_subnet JSON Request contains subnet_id options_list Case: Incorrect subnet id sending a subnet id which will not exist in the dhcp4 Passes only if 1. FAST Type Response statusCode is 9000094014 2. FAST Type Response statusValue is 'Failed to add subnet option due to an issue with KEA server response' 3. Length should be -1 since subnet id is incorrect 4. FAST Type Response data will have error as Unable to find the subnet with id {} from config obtained from server at {}:{} """ LOGGER.info('Negative Testing add_option_subnet() - Incorrect subnet id') json_req = { "subnet_id": config_nt['subnet_id']['incorrect'], "options_list": config_nt["option_data"]['valid'] } num_option_before_add_opt = get_len_subnet_options_by_id() LOGGER.info('Subnets after the Add Options API call: %d', num_option_before_add_opt) response = self.app.post('/dhcp4/subnets/options/add', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) num_option_after_add_opt = get_len_subnet_options_by_id() LOGGER.info('Subnets after the Add Options API call: %d', num_option_after_add_opt) LOGGER.info('API Test Response -> %s', str(api_response_json)) self.assertEqual(api_response_json['statusCode'], '9000094014') self.assertEqual(api_response_json['statusValue'], ERROR_4014_VALUE) self.assertEqual(num_option_after_add_opt, num_option_before_add_opt, -1) self.assertEqual(api_response_json["data"]["error"], SUBNET_NOT_FOUND.format(config_nt['subnet_id']['incorrect'], DHCP_IP, DHCP_PORT)) def test_4015_add_option_subnet_invalid_option_code(self): """ Testing add subnet option api. API Path: /dhcp4/subnets/add/options API Code: 009 API Function Name: fast_dhcp.endpoints.add_option_subnet JSON Request contains subnet_id options_list Case: Invalid Options Code Sending an option code outside of the DHCP code list. Passes only if 1. FAST Type Response statusCode is 9000094015 2. FAST Type Response statusValue is 'Failed to add subnet option' 3. Number of subnets options for the id should not change """ LOGGER.info('Negative Testing add_option_subnet() - ' 'Duplicate Options Code for same id') json_req = { "subnet_id": config_nt['subnet_id']['existing'], "options_list": config_nt['option_data']['incorrect'] } num_option_before_add_opt = get_len_subnet_options_by_id() LOGGER.info('Subnets after the Add Options API call: %d', num_option_before_add_opt) response = self.app.post('/dhcp4/subnets/options/add', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) num_option_after_add_opt = get_len_subnet_options_by_id() LOGGER.info('Subnets after the Add Options API call: %d', num_option_after_add_opt) LOGGER.info('API Test Response -> %s', str(api_response_json)) self.assertEqual(api_response_json['statusCode'], '9000094015') self.assertEqual(api_response_json['statusValue'], ERROR_4015_VALUE) self.assertEqual(num_option_before_add_opt, num_option_after_add_opt) def test_4016_delete_option_subnet_invalid_option_code(self): """ Testing remove subnet option api based on codes. API Path: /dhcp4/subnets/options/delete API Code: 010 API Function Name: fast_dhcp.endpoints.delete_option_subnet Case: Incorrect Options Code Sending an option code outside of the DHCP code list. JSON Request contains subnet_id codes Passes only if 1. FAST Type Response statusCode is 9000094016 2. FAST Type Response statusValue is 'Failed to remove subnet option due to an issue with KEA server response' 3. Number of subnets options for the id should not change 4. FAST Type Response data will have error as 'Specified option code(s) do not exist' """ LOGGER.info('Negative Testing delete_option_subnet() - Incorrect Options Code') num_option_before_rm_opt = get_len_subnet_options_by_id() LOGGER.info('Subnets before the remove Options API call: %d', num_option_before_rm_opt) json_req = { "subnet_id": config_nt['subnet_id']['existing'], "codes": [ config_nt['option_data']['incorrect'][0]['code'] ] } response = self.app.post('/dhcp4/subnets/options/delete', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) num_option_after_rm_opt = get_len_subnet_options_by_id() LOGGER.info('Subnets after the Add Options API call: %d', num_option_after_rm_opt) self.assertEqual(num_option_before_rm_opt, num_option_after_rm_opt) self.assertEqual(api_response_json['statusCode'], '9000104016') self.assertEqual(api_response_json['statusValue'], ERROR_4016_VALUE) self.assertEqual(api_response_json['data']['error'], OPTIONS_NOT_FOUND) def test_4016_delete_option_subnet_incorrect_subnet_id(self): """ Testing remove subnet id option api based on codes. API Path: /dhcp4/subnets/options/delete API Code: 010 API Function Name: fast_dhcp.endpoints.delete_option_subnet JSON Request contains subnet_id codes Case: Incorrect subnet id sending a subnet id which will not exist in the dhcp4 Passes only if 1. FAST Type Response statusCode is 9000104016 2. FAST Type Response statusValue is 'Failed to remove subnet option due to an issue with KEA server response' 3. Number of subnets options for the id should not change 4. FAST Type Response data will have error as Unable to find the subnet with id {} from config obtained from server at {}:{} """ LOGGER.info('Negative Testing delete_option_subnet() - Incorrect subnet id ') num_option_before_rm_opt = get_len_subnet_options_by_id() LOGGER.info('Subnets before the remove Options API call: %d', num_option_before_rm_opt) json_req = { "subnet_id": config_nt['subnet_id']['incorrect'], "codes": [ config_nt['option_data']['valid'][0]['code'] ] } response = self.app.post('/dhcp4/subnets/options/delete', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) num_option_after_rm_opt = get_len_subnet_options_by_id() LOGGER.info('Subnets after the Add Options API call: %d', num_option_after_rm_opt) self.assertEqual(api_response_json['statusCode'], '9000104016') self.assertEqual(api_response_json['statusValue'], ERROR_4016_VALUE) self.assertEqual(api_response_json["data"]["error"], SUBNET_NOT_FOUND.format(config_nt['subnet_id']['incorrect'], DHCP_IP, DHCP_PORT)) self.assertEqual(num_option_before_rm_opt, num_option_after_rm_opt) def test_4016_delete_option_subnet_empty_code_list(self): """ Testing remove subnet id option api based on codes. API Path: /dhcp4/subnets/options/delete API Code: 010 API Function Name: fast_dhcp.endpoints.delete_option_subnet JSON Request contains subnet_id codes Case: Empty Code List Sending an empty list in codes Passes only if 1. FAST Type Response statusCode is 9000094016 2. FAST Type Response statusValue is 'Failed to remove subnet option due to an issue with KEA server response' 3. Number of subnets options for the id should not change 4. FAST Type Response data will have error as 'Specified option code(s) do not exist' """ LOGGER.info('Negative Testing delete_option_subnet() - Empty Code List ') num_option_before_rm_opt = get_len_subnet_options_by_id() LOGGER.info('Subnets before the remove Options API call: %d', num_option_before_rm_opt) json_req = { "subnet_id": config_nt['subnet_id']['existing'], "codes": [] } response = self.app.post('/dhcp4/subnets/options/delete', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) num_option_after_rm_opt = get_len_subnet_options_by_id() LOGGER.info('Subnets after the Add Options API call: %d', num_option_after_rm_opt) self.assertEqual(num_option_before_rm_opt, num_option_after_rm_opt) self.assertEqual(api_response_json['statusCode'], '9000104016') self.assertEqual(api_response_json['statusValue'], ERROR_4016_VALUE) self.assertEqual(api_response_json['data']['error'], OPTIONS_NOT_FOUND) def test_4018_add_subnet_reservation_option_incorrect_subnet_id(self): """ Testing add subnet id reservations option api. API Path: /dhcp4/subnets/reservation/options/add API Code: 011 API Function Name: fast_dhcp.endpoints.add_reserv_option_subnet JSON Request contains subnet_id mac_address options_list Case: Incorrect subnet id sending a subnet id which will not exist in the dhcp4 Passes only if 1. FAST Type Response statusCode is 9000114018 2. FAST Type Response statusValue is Failed to add subnet reservation option due to an issue with KEA server response 3. FAST Type Response data will have error as Unable to find the subnet with id {} from config obtained from server at {}:{} """ LOGGER.info('Negative Testing add_reserv_option_subnet() - incorrect subnet id') json_req = { "subnet_id": config_nt['subnet_id']['incorrect'], "mac": config_nt['mac']['valid'], "options_list": config_nt["option_data"]['valid'] } response = self.app.post('/dhcp4/subnets/reservation/options/add', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) self.assertEqual(api_response_json['statusCode'], '9000114018') self.assertEqual(api_response_json['statusValue'], ERROR_4018_VALUE) self.assertEqual(api_response_json["data"]["error"], SUBNET_NOT_FOUND.format(config_nt['subnet_id']['incorrect'], DHCP_IP, DHCP_PORT)) def test_4018_add_subnet_reservation_option_incorrect_mac_add(self): """ Testing add subnet id reservations option api. API Path: /dhcp4/subnets/reservation/options/add API Code: 011 API Function Name: fast_dhcp.endpoints.add_reserv_option_subnet JSON Request contains subnet_id mac_address options_list Case: Incorrect Mac Address Sending a mac address which does not exist. Passes only if 1. FAST Type Response statusCode is 9000114018 2. FAST Type Response statusValue is "Failed to add subnet reservation option due to an issue with KEA server response" 3. Number of subnets reservations options for the id and mac address should be -1 4. FAST Type Response data has error as Specified reservation mac(s) do not exist """ LOGGER.info('Positive Testing add_reserv_option_subnet() ' '- Incorrect Mac Address') num_reserve_option_before_add_opt = \ get_len_subnet_reserv_options_by_id_and_mac() LOGGER.info('Subnets before the add reserv Options API call: %s', str(num_reserve_option_before_add_opt)) json_req = { "subnet_id": config_nt['subnet_id']['existing'], "mac": config_nt['mac']['valid'], "options_list": config_nt["option_data"]['valid'] } response = self.app.post('/dhcp4/subnets/reservation/options/add', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) num_reserve_option_after_add_opt = \ get_len_subnet_reserv_options_by_id_and_mac() LOGGER.info('Subnets after the add reserv Options API call: %s', str(num_reserve_option_after_add_opt)) self.assertEqual(num_reserve_option_after_add_opt, num_reserve_option_before_add_opt, -1) self.assertEqual(api_response_json['statusCode'], '9000114018') self.assertEqual(api_response_json['statusValue'], ERROR_4018_VALUE) self.assertEqual(api_response_json['data']['error'], RESERVATION_NOT_FOUND) def test_4019_add_subnet_reservation_option_invalid_option_code(self): """ Testing add subnet id reservations option api. API Path: /dhcp4/subnets/reservation/options/add API Code: 011 API Function Name: fast_dhcp.endpoints.add_reserv_option_subnet JSON Request contains subnet_id mac_address options_list Case: Invalid option Code Sending an option code outside of the DHCP code list. Passes only if 1. FAST Type Response statusCode is 9000114019 2. FAST Type Response statusValue is 'Failed to add subnet reservation option' 3. Number of subnets reservations options for the id and mac address should be -1 """ LOGGER.info('Negative Testing add_reserv_option_subnet() - Duplicate Code') json_req = { "subnet_id": config_nt['subnet_id']['existing'], "mac": config_nt['mac']['existing'], "options_list": config_nt["option_data"]['incorrect'] } num_reserve_option_before_add_opt = \ get_len_subnet_reserv_options_by_id_and_mac() LOGGER.info('Subnets before the add reserv Options API call: %d', num_reserve_option_before_add_opt) LOGGER.info('Second API Call for duplication') response = self.app.post('/dhcp4/subnets/reservation/options/add', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) num_reserve_option_after_add_opt = \ get_len_subnet_reserv_options_by_id_and_mac() LOGGER.info('Subnets after the add reserv Options API call: %d', num_reserve_option_after_add_opt) self.assertEqual(api_response_json['statusCode'], '9000114019') self.assertEqual(api_response_json['statusValue'], ERROR_4019_VALUE) self.assertEqual(num_reserve_option_after_add_opt, num_reserve_option_before_add_opt, -1) def test_4020_delete_subnet_reservation_option_incorrect_subnet_id(self): """ Testing remove subnet id option api based on codes. API Path: /dhcp4/subnets/reservation/options/delete API Code: 012 API Function Name: fast_dhcp.endpoints.delete_reserv_option_subnet JSON Request contains subnet_id mac_address options_list Case: Incorrect subnet id sending a subnet id which will not exist in the dhcp4 Passes only if 1. FAST Type Response statusCode is 9000124020 2. FAST Type Response statusValue is 'Failed to remove subnet reservation option due to an issue with KEA server response' 3. Number of subnets reservations options for the id and mac address should not change """ LOGGER.info('Negative Testing delete_reserv_option_subnet() ' '- Incorrect subnet id ') json_req = { "subnet_id": config_nt['subnet_id']['incorrect'], "mac": config_nt['mac']['existing'], "codes": [ config_nt["option_data"]['valid'][0]['code'] ] } response = self.app.post('/dhcp4/subnets/reservation/options/delete', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) self.assertEqual(api_response_json['statusCode'], '9000124020') self.assertEqual(api_response_json['statusValue'], ERROR_4020_VALUE) self.assertEqual(api_response_json["data"]["error"], SUBNET_NOT_FOUND.format(config_nt['subnet_id']['incorrect'], DHCP_IP, DHCP_PORT)) def test_4020_delete_subnet_reservation_option_subnet_empty_code_list(self): """ Testing remove subnet id option api based on codes. API Path: /dhcp4/subnets/reservation/options/delete API Code: 012 API Function Name: fast_dhcp.endpoints.delete_reserv_option_subnet JSON Request contains subnet_id mac_address options_list Case: Empty code list Sending an empty list in codes Passes only if 1. Number of subnets reservations options for the id and mac address should not change 2. FAST Type Response statusCode is 9000124020 3. FAST Type Response statusValue is 'Failed to remove subnet reservation option due to an issue with KEA server response' 4. FAST Type Response data has error as Specified option code(s) do not exist """ LOGGER.info('Positive Testing delete_reserv_option_subnet()') num_reserve_option_before_rm_opt = \ get_len_subnet_reserv_options_by_id_and_mac() LOGGER.info('Subnets before the remove reserv Options API call: %d', num_reserve_option_before_rm_opt) json_req = { "subnet_id": config_nt['subnet_id']['existing'], "mac": config_nt["mac"]['existing'], "codes": [] } response = self.app.post('/dhcp4/subnets/reservation/options/delete', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) num_reserve_option_after_rm_opt = \ get_len_subnet_reserv_options_by_id_and_mac() LOGGER.info('Subnets after the remove reserv Options API call: %d', num_reserve_option_after_rm_opt) self.assertEqual(api_response_json['statusCode'], '9000124020') self.assertEqual(api_response_json['statusValue'], ERROR_4020_VALUE) self.assertEqual(api_response_json['data']['error'], OPTIONS_NOT_FOUND) self.assertEqual(num_reserve_option_before_rm_opt, num_reserve_option_after_rm_opt) def test_4020_delete_subnet_reservation_option_subnet_incorrect_mac_add(self): """ Testing remove subnet id option api based on codes. API Path: /dhcp4/subnets/reservation/options/delete API Code: 012 API Function Name: fast_dhcp.endpoints.delete_reserv_option_subnet JSON Request contains subnet_id mac_address options_list Case: Incorrect Mac Address Sending a mac address which does not exist. Passes only if 1. FAST Type Response statusCode is 9000124020 2. FAST Type Response statusValue is 'Failed to remove subnet reservation option due to an issue with KEA server response' 3. Number of subnets reservations options for the id and mac address should decrease 4. FAST Type Response data has error as 'Specified reservation mac(s) do not exist' """ LOGGER.info('Positive Testing delete_reserv_option_subnet()') num_reserve_option_before_rm_opt = \ get_len_subnet_reserv_options_by_id_and_mac() LOGGER.info('Subnets before the remove reserv Options API call: %d', num_reserve_option_before_rm_opt) json_req = { "subnet_id": config_nt['subnet_id']['existing'], "mac": config_nt['mac']['valid'], "codes": [ config_nt['option_data']['valid'][0]['code'] ] } response = self.app.post('/dhcp4/subnets/reservation/options/delete', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) num_reserve_option_after_rm_opt =\ get_len_subnet_reserv_options_by_id_and_mac() LOGGER.info('Subnets after the remove reserv Options API call: %d', num_reserve_option_after_rm_opt) self.assertEqual(num_reserve_option_before_rm_opt, num_reserve_option_after_rm_opt) self.assertEqual(api_response_json['statusCode'], '9000124020') self.assertEqual(api_response_json['statusValue'], ERROR_4020_VALUE) self.assertEqual(api_response_json['data']['error'], RESERVATION_NOT_FOUND) def test_4020_delete_subnet_reservation_option_subnet_incorrect_code(self): """ Testing remove subnet id option api based on codes. API Path: /dhcp4/subnets/reservation/options/delete API Code: 012 API Function Name: fast_dhcp.endpoints.delete_reserv_option_subnet JSON Request contains subnet_id mac_address options_list Case: Incorrect code Sending an option code outside of the DHCP code list. Passes only if 1. FAST Type Response statusCode is 9000124020 2. FAST Type Response statusValue is 'Failed to remove subnet reservation option due to an issue with KEA server response' 3. Number of subnets reservations options for the id and mac address should decrease 4. FAST Type Response data has error as 'Specified reservation option code(s) do not exist' """ LOGGER.info('Negative Testing delete_reserv_option_subnet() - Incorrect code') num_reserve_option_before_rm_opt = \ get_len_subnet_reserv_options_by_id_and_mac() LOGGER.info('Subnets before the remove reserv Options API call: %d', num_reserve_option_before_rm_opt) json_req = { "subnet_id": config_nt['subnet_id']['existing'], "mac": config_nt['mac']['existing'], "codes": [ config_nt['option_data']['incorrect'][0]['code'] ] } response = self.app.post('/dhcp4/subnets/reservation/options/delete', content_type='application/json', data=json.dumps(json_req)) api_response_json = json.loads(response.data) LOGGER.info('API Test Response -> %s', str(api_response_json)) num_reserve_option_after_rm_opt = \ get_len_subnet_reserv_options_by_id_and_mac() LOGGER.info('Subnets after the remove reserv Options API call: %d', num_reserve_option_after_rm_opt) self.assertEqual(num_reserve_option_before_rm_opt, num_reserve_option_after_rm_opt) self.assertEqual(api_response_json['statusCode'], '9000124020') self.assertEqual(api_response_json['statusValue'], ERROR_4020_VALUE) self.assertEqual(api_response_json['data']['error'], OPTIONS_NOT_FOUND) if __name__ == "__main__": if not TEST_LOGGING: print('Logging disabled') print('NOTE: To enable logging for testing. Change the TEST_LOGGING setting in config.ini') LOGGER.disabled = True if GIT_BACKUP or KEA_SERVER_BACKUP or BACKUP_CONFIG: print('Make sure all backups are off to avoid backing up test dhcp configs.') else: unittest.main(verbosity=2)

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110,164

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1

0

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0

7

d0fd44c2637515efa8e316aeeee39db6a02d33f6

2,261

py

Python

2017/Day1/answer.py

yabirgb/Adventofcode

8a2300b10d2e66e46d9cdec283d12a1fb1ac2448

[ "MIT" ]

1

2017-12-05T07:48:51.000Z

2017/Day1/answer.py

yabirgb/Adventofcode

8a2300b10d2e66e46d9cdec283d12a1fb1ac2448

[ "MIT" ]

null

2017/Day1/answer.py

yabirgb/Adventofcode

8a2300b10d2e66e46d9cdec283d12a1fb1ac2448

[ "MIT" ]

1

2018-12-05T12:17:21.000Z

a = """5994521226795838486188872189952551475352929145357284983463678944777228139398117649129843853837124228353689551178129353548331779783742915361343229141538334688254819714813664439268791978215553677772838853328835345484711229767477729948473391228776486456686265114875686536926498634495695692252159373971631543594656954494117149294648876661157534851938933954787612146436571183144494679952452325989212481219139686138139314915852774628718443532415524776642877131763359413822986619312862889689472397776968662148753187767793762654133429349515324333877787925465541588584988827136676376128887819161672467142579261995482731878979284573246533688835226352691122169847832943513758924194232345988726741789247379184319782387757613138742817826316376233443521857881678228694863681971445442663251423184177628977899963919997529468354953548612966699526718649132789922584524556697715133163376463256225181833257692821331665532681288216949451276844419154245423434141834913951854551253339785533395949815115622811565999252555234944554473912359674379862182425695187593452363724591541992766651311175217218144998691121856882973825162368564156726989939993412963536831593196997676992942673571336164535927371229823236937293782396318237879715612956317715187757397815346635454412183198642637577528632393813964514681344162814122588795865169788121655353319233798811796765852443424783552419541481132132344487835757888468196543736833342945718867855493422435511348343711311624399744482832385998592864795271972577548584967433917322296752992127719964453376414665576196829945664941856493768794911984537445227285657716317974649417586528395488789946689914972732288276665356179889783557481819454699354317555417691494844812852232551189751386484638428296871436139489616192954267794441256929783839652519285835238736142997245189363849356454645663151314124885661919451447628964996797247781196891787171648169427894282768776275689124191811751135567692313571663637214298625367655969575699851121381872872875774999172839521617845847358966264291175387374464425566514426499166813392768677233356646752273398541814142523651415521363267414564886379863699323887278761615927993953372779567675""" from day1 import csum, csumHalfway print("Solution to part 1: ", csum(a)) print("Solution to part 2: ", csumHalfway(a))

323

2,138

0.979655

21

2,261

105.47619

0.619048

0.011738

0.013544

0.017156

0

0.951764

0.00973

2,261

6

2,139

376.833333

0.037517

0

0.958868

0.941176

0

1

0

1

0

false

0

0.25

0

0.25

0.5

1

0

1

null

0

1

0

1

0

1

null

1

0

1

0

11

efd4877b1d9d257c02161f00d963138833a01949

57,894

py

Python

thrift/compiler/test/fixtures/complex-struct/gen-py3lite/module/lite_metadata.py

dgrnbrg-meta/fbthrift

1d5f0799ef53feeb83425b6c9c79f86aeac7d9ed

[ "Apache-2.0" ]

null

thrift/compiler/test/fixtures/complex-struct/gen-py3lite/module/lite_metadata.py

dgrnbrg-meta/fbthrift

1d5f0799ef53feeb83425b6c9c79f86aeac7d9ed

[ "Apache-2.0" ]

1

2022-03-03T09:40:25.000Z

thrift/compiler/test/fixtures/complex-struct/gen-py3lite/module/lite_metadata.py

dgrnbrg-meta/fbthrift

1d5f0799ef53feeb83425b6c9c79f86aeac7d9ed

[ "Apache-2.0" ]

null

# # Autogenerated by Thrift # # DO NOT EDIT # @generated # import apache.thrift.metadata.lite_types as _fbthrift_metadata # TODO (ffrancet): This general pattern can be optimized by using tuples and dicts # instead of re-generating thrift structs def _fbthrift_gen_metadata_struct_MyStructFloatFieldThrowExp(metadata_struct: _fbthrift_metadata.ThriftMetadata) -> _fbthrift_metadata.ThriftMetadata: qualified_name = "module.MyStructFloatFieldThrowExp" if qualified_name in metadata_struct.structs: return metadata_struct fields = [ _fbthrift_metadata.ThriftField(id=1, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I64_TYPE), name="myLongField", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=2, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_BYTE_TYPE), name="MyByteField", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=3, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE), name="myStringField", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=4, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_DOUBLE_TYPE), name="myFloatField", is_optional=False, structured_annotations=[ ]), ] struct_dict = dict(metadata_struct.structs) struct_dict[qualified_name] = _fbthrift_metadata.ThriftStruct(name=qualified_name, fields=fields, is_union=False, structured_annotations=[ ]) new_struct = metadata_struct(structs=struct_dict) # myLongField # MyByteField # myStringField # myFloatField return new_struct def gen_metadata_struct_MyStructFloatFieldThrowExp() -> _fbthrift_metadata.ThriftMetadata: return _fbthrift_gen_metadata_struct_MyStructFloatFieldThrowExp(_fbthrift_metadata.ThriftMetadata(structs={}, enums={}, exceptions={}, services={})) # TODO (ffrancet): This general pattern can be optimized by using tuples and dicts # instead of re-generating thrift structs def _fbthrift_gen_metadata_struct_MyStructMapFloatThrowExp(metadata_struct: _fbthrift_metadata.ThriftMetadata) -> _fbthrift_metadata.ThriftMetadata: qualified_name = "module.MyStructMapFloatThrowExp" if qualified_name in metadata_struct.structs: return metadata_struct fields = [ _fbthrift_metadata.ThriftField(id=1, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I64_TYPE), name="myLongField", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=2, type=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE),valueType=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_DOUBLE_TYPE))))))), name="mapListOfFloats", is_optional=False, structured_annotations=[ ]), ] struct_dict = dict(metadata_struct.structs) struct_dict[qualified_name] = _fbthrift_metadata.ThriftStruct(name=qualified_name, fields=fields, is_union=False, structured_annotations=[ ]) new_struct = metadata_struct(structs=struct_dict) # myLongField # key # val # mapListOfFloats return new_struct def gen_metadata_struct_MyStructMapFloatThrowExp() -> _fbthrift_metadata.ThriftMetadata: return _fbthrift_gen_metadata_struct_MyStructMapFloatThrowExp(_fbthrift_metadata.ThriftMetadata(structs={}, enums={}, exceptions={}, services={})) # TODO (ffrancet): This general pattern can be optimized by using tuples and dicts # instead of re-generating thrift structs def _fbthrift_gen_metadata_struct_MyStruct(metadata_struct: _fbthrift_metadata.ThriftMetadata) -> _fbthrift_metadata.ThriftMetadata: qualified_name = "module.MyStruct" if qualified_name in metadata_struct.structs: return metadata_struct fields = [ _fbthrift_metadata.ThriftField(id=1, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I64_TYPE), name="MyIntField", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=2, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE), name="MyStringField", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=3, type=_fbthrift_metadata.ThriftType(t_struct=_fbthrift_metadata.ThriftStructType(name="module.MyDataItem")), name="MyDataField", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=4, type=_fbthrift_metadata.ThriftType(t_enum=_fbthrift_metadata.ThriftEnumType(name="module.MyEnum")), name="myEnum", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=5, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_BOOL_TYPE), name="MyBoolField", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=6, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_BYTE_TYPE), name="MyByteField", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=7, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I16_TYPE), name="MyShortField", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=8, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I64_TYPE), name="MyLongField", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=9, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_FLOAT_TYPE), name="MyDoubleField", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=10, type=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_FLOAT_TYPE))), name="lDouble", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=11, type=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I16_TYPE))), name="lShort", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=12, type=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE))), name="lInteger", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=13, type=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I64_TYPE))), name="lLong", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=14, type=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE))), name="lString", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=15, type=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_BOOL_TYPE))), name="lBool", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=16, type=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_BYTE_TYPE))), name="lByte", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=17, type=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I16_TYPE),valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE))), name="mShortString", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=18, type=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE),valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE))), name="mIntegerString", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=19, type=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE),valueType=_fbthrift_metadata.ThriftType(t_struct=_fbthrift_metadata.ThriftStructType(name="module.MyStruct")))), name="mStringMyStruct", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=20, type=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE),valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_BOOL_TYPE))), name="mStringBool", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=21, type=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE),valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE))), name="mIntegerInteger", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=22, type=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE),valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_BOOL_TYPE))), name="mIntegerBool", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=23, type=_fbthrift_metadata.ThriftType(t_set=_fbthrift_metadata.ThriftSetType(valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I16_TYPE))), name="sShort", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=24, type=_fbthrift_metadata.ThriftType(t_set=_fbthrift_metadata.ThriftSetType(valueType=_fbthrift_metadata.ThriftType(t_struct=_fbthrift_metadata.ThriftStructType(name="module.MyStruct")))), name="sMyStruct", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=25, type=_fbthrift_metadata.ThriftType(t_set=_fbthrift_metadata.ThriftSetType(valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I64_TYPE))), name="sLong", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=26, type=_fbthrift_metadata.ThriftType(t_set=_fbthrift_metadata.ThriftSetType(valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE))), name="sString", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=27, type=_fbthrift_metadata.ThriftType(t_set=_fbthrift_metadata.ThriftSetType(valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_BYTE_TYPE))), name="sByte", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=28, type=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE))),valueType=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE))))), name="mListList", is_optional=False, structured_annotations=[ ]), ] struct_dict = dict(metadata_struct.structs) struct_dict[qualified_name] = _fbthrift_metadata.ThriftStruct(name=qualified_name, fields=fields, is_union=False, structured_annotations=[ ]) new_struct = metadata_struct(structs=struct_dict) # MyIntField # MyStringField new_struct = _fbthrift_gen_metadata_struct_MyDataItem(new_struct) # MyDataField new_struct = _fbthrift_gen_metadata_enum_MyEnum(new_struct) # myEnum # MyBoolField # MyByteField # MyShortField # MyLongField # MyDoubleField # lDouble # lShort # lInteger # lLong # lString # lBool # lByte # key # val # mShortString # key # val # mIntegerString # key new_struct = _fbthrift_gen_metadata_struct_MyStruct(new_struct) # val # mStringMyStruct # key # val # mStringBool # key # val # mIntegerInteger # key # val # mIntegerBool # sShort new_struct = _fbthrift_gen_metadata_struct_MyStruct(new_struct) # sMyStruct # sLong # sString # sByte # key # val # mListList return new_struct def gen_metadata_struct_MyStruct() -> _fbthrift_metadata.ThriftMetadata: return _fbthrift_gen_metadata_struct_MyStruct(_fbthrift_metadata.ThriftMetadata(structs={}, enums={}, exceptions={}, services={})) # TODO (ffrancet): This general pattern can be optimized by using tuples and dicts # instead of re-generating thrift structs def _fbthrift_gen_metadata_struct_SimpleStruct(metadata_struct: _fbthrift_metadata.ThriftMetadata) -> _fbthrift_metadata.ThriftMetadata: qualified_name = "module.SimpleStruct" if qualified_name in metadata_struct.structs: return metadata_struct fields = [ _fbthrift_metadata.ThriftField(id=1, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I64_TYPE), name="age", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=2, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE), name="name", is_optional=False, structured_annotations=[ ]), ] struct_dict = dict(metadata_struct.structs) struct_dict[qualified_name] = _fbthrift_metadata.ThriftStruct(name=qualified_name, fields=fields, is_union=False, structured_annotations=[ ]) new_struct = metadata_struct(structs=struct_dict) # age # name return new_struct def gen_metadata_struct_SimpleStruct() -> _fbthrift_metadata.ThriftMetadata: return _fbthrift_gen_metadata_struct_SimpleStruct(_fbthrift_metadata.ThriftMetadata(structs={}, enums={}, exceptions={}, services={})) # TODO (ffrancet): This general pattern can be optimized by using tuples and dicts # instead of re-generating thrift structs def _fbthrift_gen_metadata_struct_defaultStruct(metadata_struct: _fbthrift_metadata.ThriftMetadata) -> _fbthrift_metadata.ThriftMetadata: qualified_name = "module.defaultStruct" if qualified_name in metadata_struct.structs: return metadata_struct fields = [ _fbthrift_metadata.ThriftField(id=1, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I64_TYPE), name="myLongDFset", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=2, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I64_TYPE), name="myLongDF", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=3, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE), name="portDFset", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=4, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE), name="portNum", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=5, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_BINARY_TYPE), name="myBinaryDFset", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=6, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_BINARY_TYPE), name="myBinary", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=7, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_BYTE_TYPE), name="myByteDFSet", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=8, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_BYTE_TYPE), name="myByte", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=9, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_FLOAT_TYPE), name="myDoubleDFset", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=10, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_FLOAT_TYPE), name="myDoubleDFZero", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=12, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_FLOAT_TYPE), name="myDouble", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=13, type=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE),valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE))), name="field3", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=14, type=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_enum=_fbthrift_metadata.ThriftEnumType(name="module.MyEnum")))), name="myList", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=15, type=_fbthrift_metadata.ThriftType(t_set=_fbthrift_metadata.ThriftSetType(valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE))), name="mySet", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=16, type=_fbthrift_metadata.ThriftType(t_struct=_fbthrift_metadata.ThriftStructType(name="module.SimpleStruct")), name="simpleStruct", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=17, type=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_struct=_fbthrift_metadata.ThriftStructType(name="module.SimpleStruct")))), name="listStructDFset", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=18, type=_fbthrift_metadata.ThriftType(t_union=_fbthrift_metadata.ThriftUnionType(name="module.MyUnion")), name="myUnion", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=19, type=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_union=_fbthrift_metadata.ThriftUnionType(name="module.MyUnion")))), name="listUnionDFset", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=20, type=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE),valueType=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_struct=_fbthrift_metadata.ThriftStructType(name="module.SimpleStruct")))))), name="mapNestlistStructDfSet", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=21, type=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I64_TYPE),valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE))), name="mapJavaTypeDFset", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=22, type=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I64_TYPE),valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE))), name="emptyMap", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=23, type=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE),valueType=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE),valueType=_fbthrift_metadata.ThriftType(t_enum=_fbthrift_metadata.ThriftEnumType(name="module.MyEnum")))))), name="enumMapDFset", is_optional=False, structured_annotations=[ ]), ] struct_dict = dict(metadata_struct.structs) struct_dict[qualified_name] = _fbthrift_metadata.ThriftStruct(name=qualified_name, fields=fields, is_union=False, structured_annotations=[ ]) new_struct = metadata_struct(structs=struct_dict) # myLongDFset # myLongDF # portDFset # portNum # myBinaryDFset # myBinary # myByteDFSet # myByte # myDoubleDFset # myDoubleDFZero # myDouble # key # val # field3 new_struct = _fbthrift_gen_metadata_enum_MyEnum(new_struct) # myList # mySet new_struct = _fbthrift_gen_metadata_struct_SimpleStruct(new_struct) # simpleStruct new_struct = _fbthrift_gen_metadata_struct_SimpleStruct(new_struct) # listStructDFset new_struct = _fbthrift_gen_metadata_struct_MyUnion(new_struct) # myUnion new_struct = _fbthrift_gen_metadata_struct_MyUnion(new_struct) # listUnionDFset # key new_struct = _fbthrift_gen_metadata_struct_SimpleStruct(new_struct) # val # mapNestlistStructDfSet # key # val # mapJavaTypeDFset # key # val # emptyMap # key # key new_struct = _fbthrift_gen_metadata_enum_MyEnum(new_struct) # val # val # enumMapDFset return new_struct def gen_metadata_struct_defaultStruct() -> _fbthrift_metadata.ThriftMetadata: return _fbthrift_gen_metadata_struct_defaultStruct(_fbthrift_metadata.ThriftMetadata(structs={}, enums={}, exceptions={}, services={})) # TODO (ffrancet): This general pattern can be optimized by using tuples and dicts # instead of re-generating thrift structs def _fbthrift_gen_metadata_struct_MyStructTypeDef(metadata_struct: _fbthrift_metadata.ThriftMetadata) -> _fbthrift_metadata.ThriftMetadata: qualified_name = "module.MyStructTypeDef" if qualified_name in metadata_struct.structs: return metadata_struct fields = [ _fbthrift_metadata.ThriftField(id=1, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I64_TYPE), name="myLongField", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=2, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I64_TYPE), name="myLongTypeDef", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=3, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE), name="myStringField", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=4, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE), name="myStringTypedef", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=5, type=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I16_TYPE),valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE))), name="myMapField", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=6, type=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I16_TYPE),valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE))), name="myMapTypedef", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=7, type=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_FLOAT_TYPE))), name="myListField", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=8, type=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_FLOAT_TYPE))), name="myListTypedef", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=9, type=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I16_TYPE),valueType=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_FLOAT_TYPE))))))), name="myMapListOfTypeDef", is_optional=False, structured_annotations=[ ]), ] struct_dict = dict(metadata_struct.structs) struct_dict[qualified_name] = _fbthrift_metadata.ThriftStruct(name=qualified_name, fields=fields, is_union=False, structured_annotations=[ ]) new_struct = metadata_struct(structs=struct_dict) # myLongField # myLongTypeDef # myStringField # myStringTypedef # key # val # myMapField # key # val # myMapTypedef # myListField # myListTypedef # key # val # myMapListOfTypeDef return new_struct def gen_metadata_struct_MyStructTypeDef() -> _fbthrift_metadata.ThriftMetadata: return _fbthrift_gen_metadata_struct_MyStructTypeDef(_fbthrift_metadata.ThriftMetadata(structs={}, enums={}, exceptions={}, services={})) # TODO (ffrancet): This general pattern can be optimized by using tuples and dicts # instead of re-generating thrift structs def _fbthrift_gen_metadata_struct_MyDataItem(metadata_struct: _fbthrift_metadata.ThriftMetadata) -> _fbthrift_metadata.ThriftMetadata: qualified_name = "module.MyDataItem" if qualified_name in metadata_struct.structs: return metadata_struct fields = [ ] struct_dict = dict(metadata_struct.structs) struct_dict[qualified_name] = _fbthrift_metadata.ThriftStruct(name=qualified_name, fields=fields, is_union=False, structured_annotations=[ ]) new_struct = metadata_struct(structs=struct_dict) return new_struct def gen_metadata_struct_MyDataItem() -> _fbthrift_metadata.ThriftMetadata: return _fbthrift_gen_metadata_struct_MyDataItem(_fbthrift_metadata.ThriftMetadata(structs={}, enums={}, exceptions={}, services={})) # TODO (ffrancet): This general pattern can be optimized by using tuples and dicts # instead of re-generating thrift structs def _fbthrift_gen_metadata_struct_MyUnion(metadata_struct: _fbthrift_metadata.ThriftMetadata) -> _fbthrift_metadata.ThriftMetadata: qualified_name = "module.MyUnion" if qualified_name in metadata_struct.structs: return metadata_struct fields = [ _fbthrift_metadata.ThriftField(id=1, type=_fbthrift_metadata.ThriftType(t_enum=_fbthrift_metadata.ThriftEnumType(name="module.MyEnum")), name="myEnum", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=2, type=_fbthrift_metadata.ThriftType(t_struct=_fbthrift_metadata.ThriftStructType(name="module.MyStruct")), name="myStruct", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=3, type=_fbthrift_metadata.ThriftType(t_struct=_fbthrift_metadata.ThriftStructType(name="module.MyDataItem")), name="myDataItem", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=4, type=_fbthrift_metadata.ThriftType(t_struct=_fbthrift_metadata.ThriftStructType(name="module.ComplexNestedStruct")), name="complexNestedStruct", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=5, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I64_TYPE), name="longValue", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=6, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE), name="intValue", is_optional=False, structured_annotations=[ ]), ] struct_dict = dict(metadata_struct.structs) struct_dict[qualified_name] = _fbthrift_metadata.ThriftStruct(name=qualified_name, fields=fields, is_union=True, structured_annotations=[ ]) new_struct = metadata_struct(structs=struct_dict) new_struct = _fbthrift_gen_metadata_enum_MyEnum(new_struct) # myEnum new_struct = _fbthrift_gen_metadata_struct_MyStruct(new_struct) # myStruct new_struct = _fbthrift_gen_metadata_struct_MyDataItem(new_struct) # myDataItem new_struct = _fbthrift_gen_metadata_struct_ComplexNestedStruct(new_struct) # complexNestedStruct # longValue # intValue return new_struct def gen_metadata_struct_MyUnion() -> _fbthrift_metadata.ThriftMetadata: return _fbthrift_gen_metadata_struct_MyUnion(_fbthrift_metadata.ThriftMetadata(structs={}, enums={}, exceptions={}, services={})) # TODO (ffrancet): This general pattern can be optimized by using tuples and dicts # instead of re-generating thrift structs def _fbthrift_gen_metadata_struct_MyUnionFloatFieldThrowExp(metadata_struct: _fbthrift_metadata.ThriftMetadata) -> _fbthrift_metadata.ThriftMetadata: qualified_name = "module.MyUnionFloatFieldThrowExp" if qualified_name in metadata_struct.structs: return metadata_struct fields = [ _fbthrift_metadata.ThriftField(id=1, type=_fbthrift_metadata.ThriftType(t_enum=_fbthrift_metadata.ThriftEnumType(name="module.MyEnum")), name="myEnum", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=2, type=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_DOUBLE_TYPE))))), name="setFloat", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=3, type=_fbthrift_metadata.ThriftType(t_struct=_fbthrift_metadata.ThriftStructType(name="module.MyDataItem")), name="myDataItem", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=4, type=_fbthrift_metadata.ThriftType(t_struct=_fbthrift_metadata.ThriftStructType(name="module.ComplexNestedStruct")), name="complexNestedStruct", is_optional=False, structured_annotations=[ ]), ] struct_dict = dict(metadata_struct.structs) struct_dict[qualified_name] = _fbthrift_metadata.ThriftStruct(name=qualified_name, fields=fields, is_union=True, structured_annotations=[ ]) new_struct = metadata_struct(structs=struct_dict) new_struct = _fbthrift_gen_metadata_enum_MyEnum(new_struct) # myEnum # setFloat new_struct = _fbthrift_gen_metadata_struct_MyDataItem(new_struct) # myDataItem new_struct = _fbthrift_gen_metadata_struct_ComplexNestedStruct(new_struct) # complexNestedStruct return new_struct def gen_metadata_struct_MyUnionFloatFieldThrowExp() -> _fbthrift_metadata.ThriftMetadata: return _fbthrift_gen_metadata_struct_MyUnionFloatFieldThrowExp(_fbthrift_metadata.ThriftMetadata(structs={}, enums={}, exceptions={}, services={})) # TODO (ffrancet): This general pattern can be optimized by using tuples and dicts # instead of re-generating thrift structs def _fbthrift_gen_metadata_struct_ComplexNestedStruct(metadata_struct: _fbthrift_metadata.ThriftMetadata) -> _fbthrift_metadata.ThriftMetadata: qualified_name = "module.ComplexNestedStruct" if qualified_name in metadata_struct.structs: return metadata_struct fields = [ _fbthrift_metadata.ThriftField(id=1, type=_fbthrift_metadata.ThriftType(t_set=_fbthrift_metadata.ThriftSetType(valueType=_fbthrift_metadata.ThriftType(t_set=_fbthrift_metadata.ThriftSetType(valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE))))), name="setOfSetOfInt", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=2, type=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_enum=_fbthrift_metadata.ThriftEnumType(name="module.MyEnum")))))))))), name="listofListOfListOfListOfEnum", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=3, type=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_struct=_fbthrift_metadata.ThriftStructType(name="module.MyStruct")))))), name="listOfListOfMyStruct", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=4, type=_fbthrift_metadata.ThriftType(t_set=_fbthrift_metadata.ThriftSetType(valueType=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I64_TYPE))))))), name="setOfListOfListOfLong", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=5, type=_fbthrift_metadata.ThriftType(t_set=_fbthrift_metadata.ThriftSetType(valueType=_fbthrift_metadata.ThriftType(t_set=_fbthrift_metadata.ThriftSetType(valueType=_fbthrift_metadata.ThriftType(t_set=_fbthrift_metadata.ThriftSetType(valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I64_TYPE))))))), name="setOfSetOfsetOfLong", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=6, type=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE),valueType=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_struct=_fbthrift_metadata.ThriftStructType(name="module.MyStruct")))))))), name="mapStructListOfListOfLong", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=7, type=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_struct=_fbthrift_metadata.ThriftStructType(name="module.MyStruct")),valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE))), name="mKeyStructValInt", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=8, type=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE),valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE))))), name="listOfMapKeyIntValInt", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=9, type=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE),valueType=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_struct=_fbthrift_metadata.ThriftStructType(name="module.MyStruct")))))))), name="listOfMapKeyStrValList", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=10, type=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_set=_fbthrift_metadata.ThriftSetType(valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE))),valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I64_TYPE))), name="mapKeySetValLong", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=11, type=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE))),valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE))), name="mapKeyListValLong", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=12, type=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE),valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE))),valueType=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE),valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE))))), name="mapKeyMapValMap", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=13, type=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_set=_fbthrift_metadata.ThriftSetType(valueType=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE))))),valueType=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_set=_fbthrift_metadata.ThriftSetType(valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE))))),valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE))))), name="mapKeySetValMap", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=14, type=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE),valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE))),valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE))),valueType=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE),valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE))))), name="NestedMaps", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=15, type=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE),valueType=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_struct=_fbthrift_metadata.ThriftStructType(name="module.MyStruct")))))), name="mapKeyIntValList", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=16, type=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE),valueType=_fbthrift_metadata.ThriftType(t_set=_fbthrift_metadata.ThriftSetType(valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_BOOL_TYPE))))), name="mapKeyIntValSet", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=17, type=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_set=_fbthrift_metadata.ThriftSetType(valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_BOOL_TYPE))),valueType=_fbthrift_metadata.ThriftType(t_enum=_fbthrift_metadata.ThriftEnumType(name="module.MyEnum")))), name="mapKeySetValInt", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=18, type=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE))),valueType=_fbthrift_metadata.ThriftType(t_set=_fbthrift_metadata.ThriftSetType(valueType=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_FLOAT_TYPE),valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE))))))), name="mapKeyListValSet", is_optional=False, structured_annotations=[ ]), ] struct_dict = dict(metadata_struct.structs) struct_dict[qualified_name] = _fbthrift_metadata.ThriftStruct(name=qualified_name, fields=fields, is_union=False, structured_annotations=[ ]) new_struct = metadata_struct(structs=struct_dict) # setOfSetOfInt new_struct = _fbthrift_gen_metadata_enum_MyEnum(new_struct) # listofListOfListOfListOfEnum new_struct = _fbthrift_gen_metadata_struct_MyStruct(new_struct) # listOfListOfMyStruct # setOfListOfListOfLong # setOfSetOfsetOfLong # key new_struct = _fbthrift_gen_metadata_struct_MyStruct(new_struct) # val # mapStructListOfListOfLong new_struct = _fbthrift_gen_metadata_struct_MyStruct(new_struct) # key # val # mKeyStructValInt # key # val # listOfMapKeyIntValInt # key new_struct = _fbthrift_gen_metadata_struct_MyStruct(new_struct) # val # listOfMapKeyStrValList # key # val # mapKeySetValLong # key # val # mapKeyListValLong # key # val # key # key # val # val # mapKeyMapValMap # key # key # val # val # mapKeySetValMap # key # val # key # val # key # key # val # val # NestedMaps # key new_struct = _fbthrift_gen_metadata_struct_MyStruct(new_struct) # val # mapKeyIntValList # key # val # mapKeyIntValSet # key new_struct = _fbthrift_gen_metadata_enum_MyEnum(new_struct) # val # mapKeySetValInt # key # key # val # val # mapKeyListValSet return new_struct def gen_metadata_struct_ComplexNestedStruct() -> _fbthrift_metadata.ThriftMetadata: return _fbthrift_gen_metadata_struct_ComplexNestedStruct(_fbthrift_metadata.ThriftMetadata(structs={}, enums={}, exceptions={}, services={})) # TODO (ffrancet): This general pattern can be optimized by using tuples and dicts # instead of re-generating thrift structs def _fbthrift_gen_metadata_struct_TypeRemapped(metadata_struct: _fbthrift_metadata.ThriftMetadata) -> _fbthrift_metadata.ThriftMetadata: qualified_name = "module.TypeRemapped" if qualified_name in metadata_struct.structs: return metadata_struct fields = [ _fbthrift_metadata.ThriftField(id=1, type=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I64_TYPE),valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE))), name="lsMap", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=2, type=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE),valueType=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE),valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I64_TYPE))))), name="ioMap", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=3, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE), name="BigInteger", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=4, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_BINARY_TYPE), name="binaryTestBuffer", is_optional=False, structured_annotations=[ ]), ] struct_dict = dict(metadata_struct.structs) struct_dict[qualified_name] = _fbthrift_metadata.ThriftStruct(name=qualified_name, fields=fields, is_union=False, structured_annotations=[ ]) new_struct = metadata_struct(structs=struct_dict) # key # val # lsMap # key # key # val # val # ioMap # BigInteger # binaryTestBuffer return new_struct def gen_metadata_struct_TypeRemapped() -> _fbthrift_metadata.ThriftMetadata: return _fbthrift_gen_metadata_struct_TypeRemapped(_fbthrift_metadata.ThriftMetadata(structs={}, enums={}, exceptions={}, services={})) # TODO (ffrancet): This general pattern can be optimized by using tuples and dicts # instead of re-generating thrift structs def _fbthrift_gen_metadata_exception_emptyXcep(metadata_struct: _fbthrift_metadata.ThriftMetadata) -> _fbthrift_metadata.ThriftMetadata: qualified_name = "module.emptyXcep" if qualified_name in metadata_struct.exceptions: return metadata_struct fields = [ ] struct_dict = dict(metadata_struct.exceptions) struct_dict[qualified_name] = _fbthrift_metadata.ThriftException(name=qualified_name, fields=fields, structured_annotations=[ ]) new_struct = metadata_struct(exceptions=struct_dict) return new_struct def gen_metadata_exception_emptyXcep() -> _fbthrift_metadata.ThriftMetadata: return _fbthrift_gen_metadata_exception_emptyXcep(_fbthrift_metadata.ThriftMetadata(structs={}, enums={}, exceptions={}, services={})) # TODO (ffrancet): This general pattern can be optimized by using tuples and dicts # instead of re-generating thrift structs def _fbthrift_gen_metadata_exception_reqXcep(metadata_struct: _fbthrift_metadata.ThriftMetadata) -> _fbthrift_metadata.ThriftMetadata: qualified_name = "module.reqXcep" if qualified_name in metadata_struct.exceptions: return metadata_struct fields = [ _fbthrift_metadata.ThriftField(id=1, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE), name="message", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=2, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE), name="errorCode", is_optional=False, structured_annotations=[ ]), ] struct_dict = dict(metadata_struct.exceptions) struct_dict[qualified_name] = _fbthrift_metadata.ThriftException(name=qualified_name, fields=fields, structured_annotations=[ ]) new_struct = metadata_struct(exceptions=struct_dict) # message # errorCode return new_struct def gen_metadata_exception_reqXcep() -> _fbthrift_metadata.ThriftMetadata: return _fbthrift_gen_metadata_exception_reqXcep(_fbthrift_metadata.ThriftMetadata(structs={}, enums={}, exceptions={}, services={})) # TODO (ffrancet): This general pattern can be optimized by using tuples and dicts # instead of re-generating thrift structs def _fbthrift_gen_metadata_exception_optXcep(metadata_struct: _fbthrift_metadata.ThriftMetadata) -> _fbthrift_metadata.ThriftMetadata: qualified_name = "module.optXcep" if qualified_name in metadata_struct.exceptions: return metadata_struct fields = [ _fbthrift_metadata.ThriftField(id=1, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE), name="message", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=2, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I32_TYPE), name="errorCode", is_optional=False, structured_annotations=[ ]), ] struct_dict = dict(metadata_struct.exceptions) struct_dict[qualified_name] = _fbthrift_metadata.ThriftException(name=qualified_name, fields=fields, structured_annotations=[ ]) new_struct = metadata_struct(exceptions=struct_dict) # message # errorCode return new_struct def gen_metadata_exception_optXcep() -> _fbthrift_metadata.ThriftMetadata: return _fbthrift_gen_metadata_exception_optXcep(_fbthrift_metadata.ThriftMetadata(structs={}, enums={}, exceptions={}, services={})) # TODO (ffrancet): This general pattern can be optimized by using tuples and dicts # instead of re-generating thrift structs def _fbthrift_gen_metadata_exception_complexException(metadata_struct: _fbthrift_metadata.ThriftMetadata) -> _fbthrift_metadata.ThriftMetadata: qualified_name = "module.complexException" if qualified_name in metadata_struct.exceptions: return metadata_struct fields = [ _fbthrift_metadata.ThriftField(id=1, type=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE), name="message", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=2, type=_fbthrift_metadata.ThriftType(t_list=_fbthrift_metadata.ThriftListType(valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE))), name="listStrings", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=3, type=_fbthrift_metadata.ThriftType(t_enum=_fbthrift_metadata.ThriftEnumType(name="module.MyEnum")), name="errorEnum", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=4, type=_fbthrift_metadata.ThriftType(t_union=_fbthrift_metadata.ThriftUnionType(name="module.MyUnion")), name="unionError", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=5, type=_fbthrift_metadata.ThriftType(t_struct=_fbthrift_metadata.ThriftStructType(name="module.MyStruct")), name="structError", is_optional=False, structured_annotations=[ ]), _fbthrift_metadata.ThriftField(id=6, type=_fbthrift_metadata.ThriftType(t_map=_fbthrift_metadata.ThriftMapType(keyType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_I64_TYPE),valueType=_fbthrift_metadata.ThriftType(t_primitive=_fbthrift_metadata.ThriftPrimitiveType.THRIFT_STRING_TYPE))), name="lsMap", is_optional=False, structured_annotations=[ ]), ] struct_dict = dict(metadata_struct.exceptions) struct_dict[qualified_name] = _fbthrift_metadata.ThriftException(name=qualified_name, fields=fields, structured_annotations=[ ]) new_struct = metadata_struct(exceptions=struct_dict) # message # listStrings new_struct = _fbthrift_gen_metadata_enum_MyEnum(new_struct) # errorEnum new_struct = _fbthrift_gen_metadata_struct_MyUnion(new_struct) # unionError new_struct = _fbthrift_gen_metadata_struct_MyStruct(new_struct) # structError # key # val # lsMap return new_struct def gen_metadata_exception_complexException() -> _fbthrift_metadata.ThriftMetadata: return _fbthrift_gen_metadata_exception_complexException(_fbthrift_metadata.ThriftMetadata(structs={}, enums={}, exceptions={}, services={})) def _fbthrift_gen_metadata_enum_MyEnum(metadata_struct: _fbthrift_metadata.ThriftMetadata) -> _fbthrift_metadata.ThriftMetadata: qualified_name = "module.MyEnum" if qualified_name in metadata_struct.enums: return metadata_struct elements = { 0: "MyValue1", 1: "MyValue2", 3: "MyValue3", 4: "MyValue4", 5: "MyValue5", } enum_dict = dict(metadata_struct.enums) enum_dict[qualified_name] = _fbthrift_metadata.ThriftEnum(name=qualified_name, elements=elements, structured_annotations=[]) new_struct = metadata_struct(enums=enum_dict) return new_struct def gen_metadata_enum_MyEnum() -> _fbthrift_metadata.ThriftMetadata: return _fbthrift_gen_metadata_enum_MyEnum(_fbthrift_metadata.ThriftMetadata(structs={}, enums={}, exceptions={}, services={})) def getThriftModuleMetadata() -> _fbthrift_metadata.ThriftMetadata: meta = _fbthrift_metadata.ThriftMetadata(structs={}, enums={}, exceptions={}, services={}) meta = _fbthrift_gen_metadata_enum_MyEnum(meta) meta = _fbthrift_gen_metadata_struct_MyStructFloatFieldThrowExp(meta) meta = _fbthrift_gen_metadata_struct_MyStructMapFloatThrowExp(meta) meta = _fbthrift_gen_metadata_struct_MyStruct(meta) meta = _fbthrift_gen_metadata_struct_SimpleStruct(meta) meta = _fbthrift_gen_metadata_struct_defaultStruct(meta) meta = _fbthrift_gen_metadata_struct_MyStructTypeDef(meta) meta = _fbthrift_gen_metadata_struct_MyDataItem(meta) meta = _fbthrift_gen_metadata_struct_MyUnion(meta) meta = _fbthrift_gen_metadata_struct_MyUnionFloatFieldThrowExp(meta) meta = _fbthrift_gen_metadata_struct_ComplexNestedStruct(meta) meta = _fbthrift_gen_metadata_struct_TypeRemapped(meta) meta = _fbthrift_gen_metadata_exception_emptyXcep(meta) meta = _fbthrift_gen_metadata_exception_reqXcep(meta) meta = _fbthrift_gen_metadata_exception_optXcep(meta) meta = _fbthrift_gen_metadata_exception_complexException(meta) return meta

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0.887499

0.862188

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57,894

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970

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0.83858

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efe846f6eae243f85b55877acebd1123560076d0

67,490

py

Python

tests/test_tabula_mfh.py

Ja98/TEASER

1bb782a01ce1b38c4abecb9c6ecc4d59f1ba21a3

[ "MIT" ]

75

2016-05-24T19:27:31.000Z

2022-03-22T08:12:39.000Z

tests/test_tabula_mfh.py

Ja98/TEASER

1bb782a01ce1b38c4abecb9c6ecc4d59f1ba21a3

[ "MIT" ]

427

2016-05-24T12:07:52.000Z

2022-01-11T12:56:40.000Z

tests/test_tabula_mfh.py

Ja98/TEASER

1bb782a01ce1b38c4abecb9c6ecc4d59f1ba21a3

[ "MIT" ]

60

2016-05-24T15:33:06.000Z

2021-12-23T15:00:20.000Z

from teaser.project import Project prj = Project(False) class Test_tabula_mfh(object): global prj def test_tabula_de_mfh_area_1859(self): """ Test for area estimation of tabula mfh """ prj.set_default() prj.data = None prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=1858, number_of_floors=2, height_of_floors=3.2, net_leased_area=677) assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].rooftops), 1) == 284.1 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].outer_walls), 1) == 749.3 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].ground_floors), 1) == 173.8 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].windows), 1) == 107 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].doors), 1) == 2.0 def test_tabula_de_mfh_area_1919(self): """ Test for area estimation of tabula mfh """ prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=1918, number_of_floors=2, height_of_floors=3.2, net_leased_area=312) assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].rooftops), 1) == 102.8 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].outer_walls), 1) == 146 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].ground_floors), 1) == 102.8 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].windows), 1) == 54.1 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].doors), 1) == 2.0 def test_tabula_de_mfh_area_1948(self): """ Test for area estimation of tabula mfh """ prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=1947, number_of_floors=2, height_of_floors=3.2, net_leased_area=385) assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].rooftops), 1) == 189.6 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].outer_walls), 1) == 325.5 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].ground_floors), 1) == 158.5 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].windows), 1) == 71.2 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].doors), 1) == 2.0 def test_tabula_de_mfh_area_1957(self): """ Test for area estimation of tabula mfh """ prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=1956, number_of_floors=2, height_of_floors=3.2, net_leased_area=632) assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].rooftops), 1) == 355.0 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].outer_walls), 1) == 462.0 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].ground_floors), 1) == 355.0 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].windows), 1) == 98.7 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].doors), 1) == 2.0 def test_tabula_de_mfh_area_1968(self): """ Test for area estimation of tabula mfh """ prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=1967, number_of_floors=2, height_of_floors=3.2, net_leased_area=3129) assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].rooftops), 1) == 971.1 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].outer_walls), 1) == 2039 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].ground_floors), 1) == 971.1 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].windows), 1) == 507.5 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].doors), 1) == 2.0 def test_tabula_de_mfh_area_1978(self): """ Test for area estimation of tabula mfh """ prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=1977, number_of_floors=2, height_of_floors=3.2, net_leased_area=469) assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].rooftops), 1) == 216.7 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].outer_walls), 1) == 336.0 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].ground_floors), 1) == 216.7 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].windows), 1) == 81.3 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].doors), 1) == 2.0 def test_tabula_de_mfh_area_1983(self): """ Test for area estimation of tabula mfh """ prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=1982, number_of_floors=2, height_of_floors=3.2, net_leased_area=654) assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].rooftops), 1) == 248.3 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].outer_walls), 1) == 447.1 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].ground_floors), 1) == 248.3 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].windows), 1) == 99.4 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].doors), 1) == 2.0 def test_tabula_de_mfh_area_1994(self): """ Test for area estimation of tabula mfh """ prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=1993, number_of_floors=2, height_of_floors=3.2, net_leased_area=778) assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].rooftops), 1) == 249.4 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].outer_walls), 1) == 774.8 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].ground_floors), 1) == 249.4 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].windows), 1) == 161.0 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].doors), 1) == 2.0 def test_tabula_de_mfh_area_2001(self): """ Test for area estimation of tabula mfh """ prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=2000, number_of_floors=2, height_of_floors=3.2, net_leased_area=835) assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].rooftops), 1) == 283.7 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].outer_walls), 1) == 695.8 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].ground_floors), 1) == 283.7 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].windows), 1) == 162.8 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].doors), 1) == 2.0 def test_tabula_de_mfh_area_2009(self): """ Test for area estimation of tabula mfh """ prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=2008, number_of_floors=2, height_of_floors=3.2, net_leased_area=2190) assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].rooftops), 1) == 588.0 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].outer_walls), 1) == 1698.0 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].ground_floors), 1) == 619.5 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].windows), 1) == 308.7 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].doors), 1) == 2.0 def test_tabula_de_mfh_area_2015(self): """ Test for area estimation of tabula mfh """ prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=2014, number_of_floors=2, height_of_floors=3.2, net_leased_area=1305) assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].rooftops), 1) == 321.1 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].outer_walls), 1) == 1193.2 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].ground_floors), 1) == 321.1 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].windows), 1) == 243.6 assert round( sum(wall.area for wall in prj.buildings[-1].thermal_zones[-1].doors), 1) == 47.9 def test_tabula_uvalue_standard_mfh_1859(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=1858, number_of_floors=2, height_of_floors=3.2, net_leased_area=219) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 2.6 - 0.21)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 2.0 - 0.17)), 1) for floor in prj.buildings[-1].thermal_zones[-1].ground_floors: if "_1_" in floor.construction_type: assert round(1 / (floor.r_conduc * floor.area), 1) == round((1 / (1 / 0.88 - 0.34)), 1) elif "_2_" in floor.construction_type: assert round(1 / (floor.r_conduc * floor.area), 1) == round((1 / (1 / 1.2 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 2.8 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 3.0 - 0.17)), 1) def test_tabula_uvalue_standard_mfh_1918(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=1918, number_of_floors=2, height_of_floors=3.2, net_leased_area=219) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 1.3 - 0.21)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 2.2 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].ground_floors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].ground_floors[-1].area), 1) == round((1 / (1 / 0.88 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 2.7 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 3.0 - 0.17)), 1) def test_tabula_uvalue_standard_mfh_1948(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=1947, number_of_floors=2, height_of_floors=3.2, net_leased_area=219) for roof in prj.buildings[-1].thermal_zones[-1].rooftops: if "_1_" in roof.construction_type: assert round(1 / (roof.r_conduc * roof.area), 1) == round((1 / (1 / 1.4 - 0.21)), 1) elif "_2_" in roof.construction_type: assert round(1 / (roof.r_conduc * roof.area), 1) == round((1 / (1 / 0.65 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 1.7 - 0.17)), 1) for floor in prj.buildings[-1].thermal_zones[-1].ground_floors: if "_1_" in floor.construction_type: assert round(1 / (floor.r_conduc * floor.area), 1) == round((1 / (1 / 0.77 - 0.34)), 1) elif "_2_" in floor.construction_type: assert round(1 / (floor.r_conduc * floor.area), 1) == round((1 / (1 / 1.0 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 3.0 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 3.0 - 0.17)), 1) def test_tabula_uvalue_standard_mfh_1957(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=1956, number_of_floors=2, height_of_floors=3.2, net_leased_area=219) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 1.08 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 1.2 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].ground_floors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].ground_floors[-1].area), 1) == round((1 / (1 / 1.33 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 3.0 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 3.0 - 0.17)), 1) def test_tabula_uvalue_standard_mfh_1968(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=1967, number_of_floors=2, height_of_floors=3.2, net_leased_area=219) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 0.51 - 0.21)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 1.2 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].ground_floors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].ground_floors[-1].area), 1) == round((1 / (1 / 1.08 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 3.0 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 3.0 - 0.17)), 1) def test_tabula_uvalue_standard_mfh_1978(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=1977, number_of_floors=2, height_of_floors=3.2, net_leased_area=219) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 0.51 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 1.0 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].ground_floors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].ground_floors[-1].area), 1) == round((1 / (1 / 0.77 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 3.0 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 4.0 - 0.17)), 1) def test_tabula_uvalue_standard_mfh_1983(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=1982, number_of_floors=2, height_of_floors=3.2, net_leased_area=219) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 0.43 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 0.8 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].ground_floors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].ground_floors[-1].area), 1) == round((1 / (1 / 0.65 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 3.0 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 4.0 - 0.17)), 1) def test_tabula_uvalue_standard_mfh_1994(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=1993, number_of_floors=2, height_of_floors=3.2, net_leased_area=219) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 0.36 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 0.6 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].ground_floors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].ground_floors[-1].area), 1) == round((1 / (1 / 0.51 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 3.0 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 4.0 - 0.17)), 1) def test_tabula_uvalue_standard_mfh_2001(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=2000, number_of_floors=2, height_of_floors=3.2, net_leased_area=219) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 0.32 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 0.4 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].ground_floors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].ground_floors[-1].area), 1) == round((1 / (1 / 0.4 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 1.9 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 2.0 - 0.17)), 1) def test_tabula_uvalue_standard_mfh_2009(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=2008, number_of_floors=2, height_of_floors=3.2, net_leased_area=219) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 0.2 - 0.21)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 0.25 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].ground_floors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].ground_floors[-1].area), 1) == round((1 / (1 / 0.32 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 1.4 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 3.0 - 0.17)), 1) def test_tabula_uvalue_standard_mfh_2015(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=2014, number_of_floors=2, height_of_floors=3.2, net_leased_area=219) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 0.2 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 0.28 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].ground_floors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].ground_floors[-1].area), 1) == round((1 / (1 / 0.35 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 1.3 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 1.8 - 0.17)), 1) def test_tabula_uvalue_standard_mfh_2100(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=2099, number_of_floors=2, height_of_floors=3.2, net_leased_area=219) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 0.25 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 0.29 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].ground_floors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].ground_floors[-1].area), 1) == round((1 / (1 / 0.29 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 1.1 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 1.3 - 0.17)), 1) def test_tabula_uvalue_retrofit_mfh_1859(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=1858, number_of_floors=2, height_of_floors=3.2, net_leased_area=219, construction_type="tabula_retrofit") assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 0.41 - 0.21)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 0.35 - 0.17)), 1) for floor in prj.buildings[-1].thermal_zones[-1].ground_floors: if "_1_" in floor.construction_type: assert round(1 / (floor.r_conduc * floor.area), 1) == round((1 / (1 / 0.29 - 0.34)), 1) elif "_2_" in floor.construction_type: assert round(1 / (floor.r_conduc * floor.area), 1) == round((1 / (1 / 0.32 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 1.6 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 1.6 - 0.17)), 1) def test_tabula_uvalue_retrofit_mfh_1918(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=1918, number_of_floors=2, height_of_floors=3.2, net_leased_area=219, construction_type="tabula_retrofit") assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 0.41 - 0.21)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 0.36 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].ground_floors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].ground_floors[-1].area), 1) == round((1 / (1 / 0.29 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 1.6 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 1.6 - 0.17)), 1) def test_tabula_uvalue_retrofit_mfh_1948(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=1947, number_of_floors=2, height_of_floors=3.2, net_leased_area=219, construction_type="tabula_retrofit") for roof in prj.buildings[-1].thermal_zones[-1].rooftops: if "_1_" in roof.construction_type: assert round(1 / (roof.r_conduc * roof.area), 1) == round((1 / (1 / 0.41 - 0.21)), 1) elif "_2_" in roof.construction_type: assert round(1 / (roof.r_conduc * roof.area), 1) == round((1 / (1 / 0.2 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 0.25 - 0.17)), 1) for floor in prj.buildings[-1].thermal_zones[-1].ground_floors: if "_1_" in floor.construction_type: assert round(1 / (floor.r_conduc * floor.area), 1) == round((1 / (1 / 0.28 - 0.34)), 1) elif "_2_" in floor.construction_type: assert round(1 / (floor.r_conduc * floor.area), 1) == round((1 / (1 / 0.3 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 1.3 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 1.3 - 0.17)), 1) def test_tabula_uvalue_retrofit_mfh_1957(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=1956, number_of_floors=2, height_of_floors=3.2, net_leased_area=219, construction_type="tabula_retrofit") assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 0.23 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 0.23 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].ground_floors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].ground_floors[-1].area), 1) == round((1 / (1 / 0.33 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 1.3 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 1.3 - 0.17)), 1) def test_tabula_uvalue_retrofit_mfh_1968(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=1967, number_of_floors=2, height_of_floors=3.2, net_leased_area=219, construction_type="tabula_retrofit") assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 0.19 - 0.21)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 0.23 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].ground_floors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].ground_floors[-1].area), 1) == round((1 / (1 / 0.31 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 1.3 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 1.3 - 0.17)), 1) def test_tabula_uvalue_retrofit_mfh_1978(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=1977, number_of_floors=2, height_of_floors=3.2, net_leased_area=219, construction_type="tabula_retrofit") assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 0.19 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 0.22 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].ground_floors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].ground_floors[-1].area), 1) == round((1 / (1 / 0.28 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 1.3 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 1.3 - 0.17)), 1) def test_tabula_uvalue_retrofit_mfh_1983(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=1982, number_of_floors=2, height_of_floors=3.2, net_leased_area=219, construction_type="tabula_retrofit") assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 0.17 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 0.21 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].ground_floors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].ground_floors[-1].area), 1) == round((1 / (1 / 0.26 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 1.3 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 1.3 - 0.17)), 1) def test_tabula_uvalue_retrofit_mfh_1994(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=1993, number_of_floors=2, height_of_floors=3.2, net_leased_area=219, construction_type="tabula_retrofit") assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 0.16 - 0.21)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 0.2 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].ground_floors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].ground_floors[-1].area), 1) == round((1 / (1 / 0.24 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 1.3 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 1.3 - 0.17)), 1) def test_tabula_uvalue_retrofit_mfh_2001(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=2000, number_of_floors=2, height_of_floors=3.2, net_leased_area=219, construction_type="tabula_retrofit") assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 0.15 - 0.21)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 0.17 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].ground_floors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].ground_floors[-1].area), 1) == round((1 / (1 / 0.21 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 1.3 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 1.3 - 0.17)), 1) def test_tabula_uvalue_retrofit_mfh_2009(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=2008, number_of_floors=2, height_of_floors=3.2, net_leased_area=219, construction_type="tabula_retrofit") assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 0.2 - 0.21)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 0.13 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].ground_floors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].ground_floors[-1].area), 1) == round((1 / (1 / 0.18 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 1.3 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 1.3 - 0.17)), 1) def test_tabula_uvalue_retrofit_mfh_2015(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=2014, number_of_floors=2, height_of_floors=3.2, net_leased_area=219, construction_type="tabula_retrofit") assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 0.1 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 0.14 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].ground_floors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].ground_floors[-1].area), 1) == round((1 / (1 / 0.18 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 0.7 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 0.8 - 0.17)), 1) def test_tabula_uvalue_retrofit_mfh_2100(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=2099, number_of_floors=2, height_of_floors=3.2, net_leased_area=219, construction_type="tabula_retrofit") assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 0.1 - 0.21)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 0.11 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].ground_floors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].ground_floors[-1].area), 1) == round((1 / (1 / 0.11 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 1.1 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 1.3 - 0.17)), 1) def test_tabula_uvalue_retrofit_adv_mfh_1859(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=1858, number_of_floors=2, height_of_floors=3.2, net_leased_area=219, construction_type="tabula_adv_retrofit") assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 0.14 - 0.21)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 0.14 - 0.17)), 1) for floor in prj.buildings[-1].thermal_zones[-1].ground_floors: if "_1_" in floor.construction_type: assert round(1 / (floor.r_conduc * floor.area), 1) == round((1 / (1 / 0.22 - 0.34)), 1) elif "_2_" in floor.construction_type: assert round(1 / (floor.r_conduc * floor.area), 1) == round((1 / (1 / 0.23 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 0.8 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 0.8 - 0.17)), 1) def test_tabula_uvalue_retrofit_adv_mfh_1918(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=1918, number_of_floors=2, height_of_floors=3.2, net_leased_area=219, construction_type="tabula_adv_retrofit") assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 0.14 - 0.21)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 0.14 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].ground_floors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].ground_floors[-1].area), 1) == round((1 / (1 / 0.22 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 0.8 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 0.8 - 0.17)), 1) def test_tabula_uvalue_retrofit_adv_mfh_1948(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=1947, number_of_floors=2, height_of_floors=3.2, net_leased_area=219, construction_type="tabula_adv_retrofit") for roof in prj.buildings[-1].thermal_zones[-1].rooftops: if "_1_" in roof.construction_type: assert round(1 / (roof.r_conduc * roof.area), 1) == round((1 / (1 / 0.14 - 0.21)), 1) elif "_2_" in roof.construction_type: assert round(1 / (roof.r_conduc * roof.area), 1) == round((1 / (1 / 0.1 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 0.13 - 0.17)), 1) for floor in prj.buildings[-1].thermal_zones[-1].ground_floors: if "_1_" in floor.construction_type: assert round(1 / (floor.r_conduc * floor.area), 1) == round((1 / (1 / 0.21 - 0.34)), 1) elif "_2_" in floor.construction_type: assert round(1 / (floor.r_conduc * floor.area), 1) == round((1 / (1 / 0.23 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 0.8 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 0.8 - 0.17)), 1) def test_tabula_uvalue_retrofit_adv_mfh_1957(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=1956, number_of_floors=2, height_of_floors=3.2, net_leased_area=219, construction_type="tabula_adv_retrofit") assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 0.11 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 0.13 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].ground_floors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].ground_floors[-1].area), 1) == round((1 / (1 / 0.24 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 0.8 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 0.8 - 0.17)), 1) def test_tabula_uvalue_retrofit_adv_mfh_1968(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=1967, number_of_floors=2, height_of_floors=3.2, net_leased_area=219, construction_type="tabula_adv_retrofit") assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 0.09 - 0.21)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 0.13 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].ground_floors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].ground_floors[-1].area), 1) == round((1 / (1 / 0.23 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 0.8 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 0.8 - 0.17)), 1) def test_tabula_uvalue_retrofit_adv_mfh_1978(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=1977, number_of_floors=2, height_of_floors=3.2, net_leased_area=219, construction_type="tabula_adv_retrofit") assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 0.09 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 0.13 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].ground_floors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].ground_floors[-1].area), 1) == round((1 / (1 / 0.21 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 0.8 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 0.8 - 0.17)), 1) def test_tabula_uvalue_retrofit_adv_mfh_1983(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=1982, number_of_floors=2, height_of_floors=3.2, net_leased_area=219, construction_type="tabula_adv_retrofit") assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 0.09 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 0.12 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].ground_floors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].ground_floors[-1].area), 1) == round((1 / (1 / 0.2 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 0.8 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 0.8 - 0.17)), 1) def test_tabula_uvalue_retrofit_adv_mfh_1994(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=1993, number_of_floors=2, height_of_floors=3.2, net_leased_area=219, construction_type="tabula_adv_retrofit") assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 0.09 - 0.21)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 0.12 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].ground_floors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].ground_floors[-1].area), 1) == round((1 / (1 / 0.19 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 0.8 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 0.8 - 0.17)), 1) def test_tabula_uvalue_retrofit_adv_mfh_2001(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=2000, number_of_floors=2, height_of_floors=3.2, net_leased_area=219, construction_type="tabula_adv_retrofit") assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 0.11 - 0.21)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 0.14 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].ground_floors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].ground_floors[-1].area), 1) == round((1 / (1 / 0.17 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 0.8 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 0.8 - 0.17)), 1) def test_tabula_uvalue_retrofit_adv_mfh_2009(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=2008, number_of_floors=2, height_of_floors=3.2, net_leased_area=219, construction_type="tabula_adv_retrofit") assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 0.14 - 0.21)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 0.14 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].ground_floors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].ground_floors[-1].area), 1) == round((1 / (1 / 0.17 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 0.8 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 0.8 - 0.17)), 1) def test_tabula_uvalue_retrofit_adv_mfh_2015(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=2014, number_of_floors=2, height_of_floors=3.2, net_leased_area=219, construction_type="tabula_adv_retrofit") assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 0.08 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 0.12 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].ground_floors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].ground_floors[-1].area), 1) == round((1 / (1 / 0.12 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 0.7 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 0.8 - 0.17)), 1) def test_tabula_uvalue_retrofit_adv_mfh_2100(self): prj.add_residential( method='tabula_de', usage='multi_family_house', name="ResidentialBuilding", year_of_construction=2099, number_of_floors=2, height_of_floors=3.2, net_leased_area=219, construction_type="tabula_adv_retrofit") assert round( 1 / (prj.buildings[-1].thermal_zones[-1].rooftops[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].rooftops[-1].area), 1) == round((1 / (1 / 0.1 - 0.21)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].outer_walls[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].outer_walls[-1].area), 1) == round((1 / (1 / 0.11 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].ground_floors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].ground_floors[-1].area), 1) == round((1 / (1 / 0.12 - 0.34)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].windows[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].windows[-1].area), 1) == round((1 / (1 / 0.7 - 0.17)), 1) assert round( 1 / (prj.buildings[-1].thermal_zones[-1].doors[-1].r_conduc * prj.buildings[-1].thermal_zones[-1].doors[-1].area), 1) == round((1 / (1 / 0.8 - 0.17)), 1)

40.853511

79

0.525396

8,909

67,490

3.791222

0.01998

0.144244

0.156265

0.240407

0.991799

0.990348

0.990319

0.990111

0.987328

0

0.087461

0.311676

67,490

1,651

80

40.878256

0.639608

0.006342

0

0.886989

0

0.039277

0

0.181413

1

0.034944

false

0

0.000743

0

0.036431

0

null

0

1

0

1

0

null

0

8

ef4c0b6cd0196641b4fa0943c98bbffe061d7bc7

1,582

py

Python

fn_reflection/typed_dict.py

fn-reflection/fn_reflection

1e2c1c812dd9d119f3e2b533a8bc5988a1f656d3

[ "Apache-2.0" ]

null

fn_reflection/typed_dict.py

fn-reflection/fn_reflection

1e2c1c812dd9d119f3e2b533a8bc5988a1f656d3

[ "Apache-2.0" ]

null

fn_reflection/typed_dict.py

fn-reflection/fn_reflection

1e2c1c812dd9d119f3e2b533a8bc5988a1f656d3

[ "Apache-2.0" ]

null

import numba def i4_0d_dict(**kvs): d = numba.typed.Dict.empty(key_type=numba.types.unicode_type, value_type=numba.types.int32) d.update(kvs) return d def i4_1d_dict(**kvs): d = numba.typed.Dict.empty(key_type=numba.types.unicode_type, value_type=numba.types.int32[:]) d.update(kvs) return d def i8_0d_dict(**kvs): d = numba.typed.Dict.empty(key_type=numba.types.unicode_type, value_type=numba.types.int64) d.update(kvs) return d def i8_1d_dict(**kvs): d = numba.typed.Dict.empty(key_type=numba.types.unicode_type, value_type=numba.types.int64[:]) d.update(kvs) return d def f4_0d_dict(**kvs): d = numba.typed.Dict.empty(key_type=numba.types.unicode_type, value_type=numba.types.float32) d.update(kvs) return d def f4_1d_dict(**kvs): d = numba.typed.Dict.empty(key_type=numba.types.unicode_type, value_type=numba.types.float32[:]) d.update(kvs) return d def f8_0d_dict(**kvs): d = numba.typed.Dict.empty(key_type=numba.types.unicode_type, value_type=numba.types.float64) d.update(kvs) return d def f8_1d_dict(**kvs): d = numba.typed.Dict.empty(key_type=numba.types.unicode_type, value_type=numba.types.float64[:]) d.update(kvs) return d i4_dict = i4_0d_dict i8_dict = i8_0d_dict f4_dict = f4_0d_dict f8_dict = f8_0d_dict

25.111111

65

0.601138

230

1,582

3.908696

0.108696

0.160178

0.249166

0.115684

0.917686

0.901001

0

0.038767

0.282554

1,582

63

66

25.111111

0.753304

0

0.533333

0

1

0.177778

false

0

0.022222

0

0.377778

0

null

0

1

0

1

0

null

0

7

327c17d4efa59a3fe88a5b4402bd494baec4fe5d

131

py

Python

model/__init__.py

Yoshi-Exeler/meiern

ade6d7c418d713c1286af33d8a597ef70effeb08

[ "MIT" ]

null

model/__init__.py

Yoshi-Exeler/meiern

ade6d7c418d713c1286af33d8a597ef70effeb08

[ "MIT" ]

null

model/__init__.py

Yoshi-Exeler/meiern

ade6d7c418d713c1286af33d8a597ef70effeb08

[ "MIT" ]

1

2022-01-24T09:53:44.000Z

from model.game import * from model.dice import * from model.die import * from model.gameconfig import * from model.player import *

26.2

30

0.778626

20

131

5.1

0.4

0.441176

0.588235

0

0.145038

131

5

31

26.2

0.910714

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

085ff597970307d647a1ed0f987634ca0b63dd2b

1,871

py

Python

M.py

rusdiahmad402/Darkid

354508ff1488beaaff7b1849f618c0ef16f1aa75

[ "Apache-2.0" ]

6

2020-05-08T23:47:53.000Z

2020-07-09T21:47:54.000Z

M.py

rusdiahmad402/Darkid

354508ff1488beaaff7b1849f618c0ef16f1aa75

[ "Apache-2.0" ]

null

M.py

rusdiahmad402/Darkid

354508ff1488beaaff7b1849f618c0ef16f1aa75

[ "Apache-2.0" ]

2

2020-06-07T17:03:22.000Z

2020-06-23T16:38:45.000Z

#Coded by:VINS #FACEBOOK:https://www.facebook.com/MrvinsT #GitHub:https://github.com/MRV1N5 #Note:Jangan di ubah ya nanti bisa error import os import sys import time import random def kntl(): load = [ '\033[1;31m[\033[1;37m#################\033[1;31m] \033[1;37m0% ', '\033[1;31m[\033[1;34m#####\033[1;37m############\033[1;31m] \033[1;37m40% ', '\033[1;31m[\033[1;34m##########\033[1;37m#######\033[1;31m] \033[1;37m60% ', '\033[1;31m[\033[1;34m###########\033[1;37m######\033[1;31m] \033[1;37m70% ', '\033[1;31m[\033[1;34m#############\033[1;37m####\033[1;31m] \033[1;37m80% ', '\033[1;31m[\033[1;34m###############\033[1;37m##\033[1;31m] \033[1;37m90% ', '\033[1;31m[\033[1;34m#################\033[1;31m] \033[1;37m100% ', '\033[1;31m[\033[1;37m SUCCESS \033[1;31m] \033[1;37m100% ', '\033[1;31m[\033[1;37m \033[1;31m] \033[1;37m100% ', '\033[1;31m[\033[1;37m SUCCESS \033[1;31m] \033[1;37m100% ', '\033[1;31m[\033[1;37m \033[1;31m] \033[1;37m100% ', '\033[1;31m[\033[1;37m SUCCESS \033[1;31m] \033[1;37m100% ', '\033[1;31m[\033[1;37m \033[1;31m] \033[1;37m100% ', '\033[1;31m[\033[1;37m SUCCESS \033[1;31m] \033[1;37m100% ', '\033[1;31m[\033[1;37m \033[1;31m] \033[1;37m100% ', '\033[1;31m[\033[1;37m SUCCESS \033[1;31m] \033[1;37m100% ', '\033[1;31m[\033[1;37m \033[1;31m] \033[1;37m100% ', '\033[1;31m[\033[1;37m SUCCESS \033[1;31m] \033[1;37m100% ', '\033[1;31m[\033[1;37m \033[1;31m] \033[1;37m100% ', '\033[1;31m[\033[1;37m SUCCESS \033[1;31m] \033[1;37m100% ', '\033[1;31m[\033[1;34m#################\033[1;31m] \033[1;37m100% '] for o in load: print '\r\x1b[1;37m [\033[1;32m+\033[1;37m] \x1b[1;92mLoading \x1b[1;97m' + o, sys.stdout.flush() time.sleep(0.3) kntl()

103.944444

1,497

0.517905

337

1,871

2.875371

0.15727

0.375645

0.303406

0.433437

0.721362

0

0.397172

0.168359

1,871

17

1,498

110.058824

0.225578

0.066809

0

1.833333

0.847876

0.423651

0

null

0

0.333333

null

0.083333

0

null

1

0

1

0

1

0

1

0

1

null

0

1

0

1

0

17

08e3576804504111d4ed1d1cb8c0cfc7faadabfe

3,767

py

Python

application/registration/forms.py

roklem314/PotilasArkisto

b005dcad4442820a265b62156ddfe61abb5b9707

[ "MIT" ]

2

2018-03-23T08:45:10.000Z

2021-01-22T11:17:14.000Z

application/registration/forms.py

roklem314/PotilasArkisto

b005dcad4442820a265b62156ddfe61abb5b9707

[ "MIT" ]

1

2018-05-07T18:56:00.000Z

2019-02-11T21:10:44.000Z

application/registration/forms.py

roklem314/Laakari-palvelu

b005dcad4442820a265b62156ddfe61abb5b9707

[ "MIT" ]

null

from flask_wtf import FlaskForm from flask_login import current_user from wtforms import StringField, PasswordField, BooleanField,SubmitField,RadioField from wtforms.validators import ValidationError, DataRequired, Email, EqualTo from application.registration.models import Accounts class RegistrationForm(FlaskForm): name = StringField('Name',validators=[DataRequired('Name is mandatory!')]) address = StringField('Address', validators=[DataRequired('Address is mandatory!')]) postal_code = StringField('Postalcode',validators=[DataRequired('Postalcode is mandatory!')]) post_office = StringField('Postoffice',validators=[DataRequired('Postoffice is mandatory!')]) email = StringField('Email', validators=[DataRequired('Email is mandatory!'), Email("Please check your email!")]) password = PasswordField('Password',validators=[DataRequired('Password is mandatory!')]) password2 = PasswordField('Password again', validators=[DataRequired('Please give password again!'),EqualTo("password")]) def validate_email(self, email): u = Accounts.query.filter_by(email=email.data).first() if u is not None: raise ValidationError('Email address is already in use!') def validate_password(self,password): if len(password.data) < 8: raise ValidationError('Password must be at least 8 characters!') class Meta: csrf = False class ModifyForm(FlaskForm): name = StringField('Name',validators=[DataRequired('Name is mandatory!')]) email = StringField('Email', validators=[DataRequired('Email is mandatory!'), Email("Please check your email!")]) password = PasswordField('Password',validators=[DataRequired('Password is mandatory!')]) password2 = PasswordField('Password again', validators=[DataRequired('Please give password again!'),EqualTo("password")]) def validate_email_password(self, email): u = Accounts.query.filter_by(email=email.data).first() if u is not None: if u.email != current_user.email: raise ValidationError('Email address is already in use!') def validate_password(self,password): u = Accounts.query.filter_by(email=current_user.email).first() if len(password.data) < 8: raise ValidationError('Password must be at least 8 characters!') if (u.password != password.data): raise ValidationError('Password is invalid!') class Meta: csrf = False class DeleteForm(FlaskForm): password = PasswordField('Confirm by entering a password',validators=[DataRequired("Password is mandatory!")]) password2 = PasswordField('Password again', validators=[DataRequired('Please give password again!'),EqualTo("password")]) def validate_password(self,password): u = Accounts.query.filter_by(email=current_user.email).first() if not (u.password == password.data): raise ValidationError('Password is invalid!') class Meta: csrf = False class DoctorRegistrationForm(FlaskForm): name = StringField('Name',validators=[DataRequired('Name is mandatory!')]) address = StringField('Address', validators=[DataRequired('Address is mandatory!')]) postal_code = StringField('Postalcode',validators=[DataRequired('Postalcode is mandatory!')]) post_office = StringField('Postoffice',validators=[DataRequired('Postoffice is mandatory!')]) email = StringField('Email', validators=[DataRequired('Email is mandatory!'), Email("Please check your email!")]) def validate_email(self, email): u = Accounts.query.filter_by(email=email.data).first() if u is not None: raise ValidationError('Email address is already in use!') class Meta: csrf = False

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0.182039

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0.170693

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1

0

null

0

1

0

1

0

9

08f0877fa8e0f9ac8db333e857c0505a2ae09876

6,825

py

Python

tests/test_utils.py

carsonmckee/bayesglm

443c65c1763fb287e7a0ad1fa516ebf92557f0b3

[ "MIT" ]

null

tests/test_utils.py

carsonmckee/bayesglm

443c65c1763fb287e7a0ad1fa516ebf92557f0b3

[ "MIT" ]

null

tests/test_utils.py

carsonmckee/bayesglm

443c65c1763fb287e7a0ad1fa516ebf92557f0b3

[ "MIT" ]

null

import unittest import sys sys.path.append('/Users/carsonmckee/Dev/bayesglm_2/bayesglm') import utils import pandas class TestModelMatrix(unittest.TestCase): def setUp(self): self.data = pandas.DataFrame(data=[[1,"A",3,4,5], [6,"B",8,9,10], [11,"C",13,14,15]], columns=["response", "x1", "x2", "x3", "x4"]) def test_all(self): expected_mat = self.data.drop(["response", "x1"], axis=1) expected_mat["Intercept"] = 1 expected_mat["x1B"] = (self.data["x1"] == "B").astype(int) expected_mat["x1C"] = (self.data["x1"] == "C").astype(int) expected_mat = expected_mat.sort_index(axis=1) res, mat = utils.model_matrix("response~.", self.data) pandas.testing.assert_frame_equal(mat.sort_index(axis=1), expected_mat) def test_all_minus_x1(self): expected_mat = self.data.drop(["response", "x1"], axis=1) expected_mat["Intercept"] = 1 expected_mat = expected_mat.sort_index(axis=1) res, mat = utils.model_matrix("response~.-x1", self.data) pandas.testing.assert_frame_equal(mat.sort_index(axis=1), expected_mat) def test_all_minus_intercept(self): expected_mat = self.data.drop(["response","x1"], axis=1) expected_mat["x1B"] = (self.data["x1"] == "B").astype(int) expected_mat["x1C"] = (self.data["x1"] == "C").astype(int) expected_mat = expected_mat.sort_index(axis=1) res, mat = utils.model_matrix("response~.-1", self.data) pandas.testing.assert_frame_equal(mat.sort_index(axis=1), expected_mat) def test_simple_add(self): expected_mat = self.data.drop(["response","x1","x3"], axis=1) expected_mat["Intercept"] = 1 expected_mat["x1B"] = (self.data["x1"] == "B").astype(int) expected_mat["x1C"] = (self.data["x1"] == "C").astype(int) expected_mat = expected_mat.sort_index(axis=1) res, mat = utils.model_matrix("response~ x1 + x2 + x4", self.data) pandas.testing.assert_frame_equal(mat.sort_index(axis=1), expected_mat) def test_all_and_subtract(self): expected_mat = self.data.drop(["response","x1","x4"], axis=1) expected_mat["x1B"] = (self.data["x1"] == "B").astype(int) expected_mat["x1C"] = (self.data["x1"] == "C").astype(int) expected_mat = expected_mat.sort_index(axis=1) res, mat = utils.model_matrix("response~. - x4 -1", self.data) pandas.testing.assert_frame_equal(mat.sort_index(axis=1), expected_mat) def test_simple_interaction(self): expected_mat = self.data.drop(["response","x1","x2", "x3", "x4"], axis=1) expected_mat["x2*x3"] = self.data["x2"]*self.data["x3"] expected_mat = expected_mat.sort_index(axis=1) res, mat = utils.model_matrix("response~ x2*x3 -1", self.data) pandas.testing.assert_frame_equal(mat.sort_index(axis=1), expected_mat) def test_multiple_interaction(self): expected_mat = self.data.drop(["response","x1","x2", "x3", "x4"], axis=1) expected_mat["x2*x3*x4"] = self.data["x2"]*self.data["x3"]*self.data["x4"] expected_mat = expected_mat.sort_index(axis=1) res, mat = utils.model_matrix("response~ x2*x3*x4 -1", self.data) pandas.testing.assert_frame_equal(mat.sort_index(axis=1), expected_mat) res, mat2 = utils.model_matrix("response~ x2*x4*x3 -1", self.data) pandas.testing.assert_frame_equal(mat2.sort_index(axis=1), expected_mat) def test_all_plus_simple_interaction(self): expected_mat = self.data.drop(["response", "x1"], axis=1) expected_mat["x2*x3"] = self.data["x2"]*self.data["x3"] expected_mat["Intercept"] = 1 expected_mat["x1B"] = (self.data["x1"] == "B").astype(int) expected_mat["x1C"] = (self.data["x1"] == "C").astype(int) expected_mat = expected_mat.sort_index(axis=1) res, mat = utils.model_matrix("response~ . + x2*x3", self.data) pandas.testing.assert_frame_equal(mat.sort_index(axis=1), expected_mat) res, mat2 = utils.model_matrix("response~ . + x3*x2", self.data) pandas.testing.assert_frame_equal(mat2.sort_index(axis=1), expected_mat) def test_all_plus_multi_interaction(self): expected_mat = self.data.drop(["response", "x1"], axis=1) expected_mat["x2*x3*x4"] = self.data["x2"]*self.data["x3"]*self.data["x4"] expected_mat["Intercept"] = 1 expected_mat["x1B"] = (self.data["x1"] == "B").astype(int) expected_mat["x1C"] = (self.data["x1"] == "C").astype(int) expected_mat = expected_mat.sort_index(axis=1) res, mat = utils.model_matrix("response~ . + x2*x3*x4", self.data) pandas.testing.assert_frame_equal(mat.sort_index(axis=1), expected_mat) res, mat2 = utils.model_matrix("response~ . + x3*x2*x4", self.data) pandas.testing.assert_frame_equal(mat2.sort_index(axis=1), expected_mat) def test_discrete_inter_discrete(self): self.data["x5"] = ["D", "E", "F"] expected_mat = self.data.drop(["response", "x1", "x2", "x3", "x4", "x5"], axis=1) expected_mat["Intercept"] = 1 expected_mat["x1B*x5E"] = (self.data["x1"] == "B").astype(int) * (self.data["x5"] == "E").astype(int) expected_mat["x1C*x5E"] = (self.data["x1"] == "C").astype(int) * (self.data["x5"] == "E").astype(int) expected_mat["x1B*x5F"] = (self.data["x1"] == "B").astype(int) * (self.data["x5"] == "F").astype(int) expected_mat["x1C*x5F"] = (self.data["x1"] == "C").astype(int) * (self.data["x5"] == "F").astype(int) expected_mat = expected_mat.sort_index(axis=1) res, mat = utils.model_matrix("response~ x1*x5", self.data) pandas.testing.assert_frame_equal(mat.sort_index(axis=1), expected_mat) res, mat2 = utils.model_matrix("response~ x5*x1", self.data) pandas.testing.assert_frame_equal(mat2.sort_index(axis=1), expected_mat) def test_discrete_inter_cont(self): expected_mat = self.data.drop(["response", "x1", "x2", "x3", "x4"], axis=1) expected_mat["Intercept"] = 1 expected_mat["x2*x1B"] = (self.data["x1"] == "B").astype(int) * self.data["x2"] expected_mat["x2*x1C"] = (self.data["x1"] == "C").astype(int) * self.data["x2"] expected_mat = expected_mat.sort_index(axis=1) res, mat = utils.model_matrix("response~ x1*x2", self.data) pandas.testing.assert_frame_equal(mat.sort_index(axis=1), expected_mat) res, mat2 = utils.model_matrix("response~ x1*x2", self.data) pandas.testing.assert_frame_equal(mat2.sort_index(axis=1), expected_mat) class TestChecks(unittest.TestCase): def test_check_distribution(self): pass if __name__ == '__main__': unittest.main()

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109

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6,825

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0.174312

0

null

1

0

1

0

null

0

7

f5c188b193ab50a6a91e00985eed8e29aeac8f11

196

py

Python

Hackergame_2020/会复读的复读机/sha256.py

Wycers/Codelib

86d83787aa577b8f2d66b5410e73102411c45e46

[ "MIT" ]

22

2018-08-07T06:55:10.000Z

2021-06-12T02:12:19.000Z

Hackergame_2020/会复读的复读机/sha256.py

Wycers/Codelib

86d83787aa577b8f2d66b5410e73102411c45e46

[ "MIT" ]

28

2020-03-04T23:47:22.000Z

2022-02-26T18:50:00.000Z

Hackergame_2020/会复读的复读机/sha256.py

Wycers/Codelib

86d83787aa577b8f2d66b5410e73102411c45e46

[ "MIT" ]

4

2019-11-09T15:41:26.000Z

2021-10-10T08:56:57.000Z

import hashlib;m = hashlib.sha256();s = 'import hashlib;m = hashlib.sha256();s = %r;m.update((s %% s).encode());print(m.hexdigest(),end="")';m.update((s % s).encode());print(m.hexdigest(),end="")

98

195

0.627551

31

196

3.967742

0.354839

0.211382

0.227642

0.341463

0.99187

0.536585

0

0.033149

0.076531

196

1

196

0.646409

0

1

0.5

0.204082

0

1

0

false

0

1

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1

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null

1

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1

0

1

0

1

0

null

0

1

0

1

0

11

eb13595fdfb9d041cd2cc367de70b507f9da732a

4,253

py

Python

tests/drf/test_drf.py

techdragon/django-auth0-auth

418de8adee28a7dc079af1ed84985239b715a258

[ "BSD-2-Clause" ]

4

2017-11-20T02:56:09.000Z

2019-06-27T13:20:54.000Z

tests/drf/test_drf.py

techdragon/django-auth0-auth

418de8adee28a7dc079af1ed84985239b715a258

[ "BSD-2-Clause" ]

1

2021-05-10T17:30:21.000Z

tests/drf/test_drf.py

techdragon/django-auth0-auth

418de8adee28a7dc079af1ed84985239b715a258

[ "BSD-2-Clause" ]

null

from selenium.webdriver.support.ui import WebDriverWait # noinspection PyPep8Naming from selenium.webdriver.support import expected_conditions as EC # noinspection PyUnresolvedReferences,PyPackageRequirements import pytest # from tests.conftest import base_url, single_page_app_test_server, javascript_frontend_config, auth0_user, \ # auth0_user_with_metadata from tests.xpaths import ( LOGIN_BUTTON, AUTH0_LOCK_LOGIN_FORM, AUTH0_LOCK_EMAIL_INPUT, AUTH0_LOCK_PASSWORD_INPUT, AUTH0_LOCK_SUBMIT_BUTTON, AUTH0_AUTHORIZE_MODAL, AUTH0_AUTHORIZE_ALLOW_BUTTON, EXTERNAL_API_PAGE_LINK, BUTTON_TO_TRIGGER_API_CALL_USING_TOKEN, EXTERNAL_API_CALL_RESULTS ) @pytest.mark.nondestructive def test_single_page_app_login(selenium, base_url, auth0_user, javascript_frontend_config, single_page_app_test_server): user_email = auth0_user['email'] user_password = auth0_user['password'] web_url = single_page_app_test_server.uri selenium.get('%s%s' % (web_url, '/')) wait = WebDriverWait(selenium, 60) # Click Login Button wait.until(EC.visibility_of_element_located(LOGIN_BUTTON)) selenium.find_element(*LOGIN_BUTTON).click() # Login Using Auth0 wait.until(EC.visibility_of_element_located(AUTH0_LOCK_LOGIN_FORM)) selenium.find_element(*AUTH0_LOCK_EMAIL_INPUT).send_keys(user_email) selenium.find_element(*AUTH0_LOCK_PASSWORD_INPUT).send_keys(user_password) selenium.find_element(*AUTH0_LOCK_SUBMIT_BUTTON).click() # TODO: This really should be using some conditional logic! wait.until(EC.visibility_of_element_located(AUTH0_AUTHORIZE_MODAL)) selenium.find_element(*AUTH0_AUTHORIZE_ALLOW_BUTTON).click() # Wait for page to load after returning to the single page app. wait.until(EC.visibility_of_element_located(EXTERNAL_API_PAGE_LINK)) selenium.find_element(*EXTERNAL_API_PAGE_LINK).click() # Wait for the button to appear after clicking on the external api page button. wait.until(EC.visibility_of_element_located(BUTTON_TO_TRIGGER_API_CALL_USING_TOKEN)) selenium.find_element(*BUTTON_TO_TRIGGER_API_CALL_USING_TOKEN).click() # Check the returned data. wait.until(EC.visibility_of_element_located(EXTERNAL_API_CALL_RESULTS)) api_result = selenium.find_element(*EXTERNAL_API_CALL_RESULTS) api_result_text = api_result.text assert '"provider": "auth0"' in str(api_result_text) @pytest.mark.nondestructive def test_single_page_app_login_with_metadata( selenium, base_url, auth0_user_with_metadata, javascript_frontend_config, single_page_app_test_server ): user_email = auth0_user_with_metadata['email'] user_password = auth0_user_with_metadata['password'] web_url = single_page_app_test_server.uri selenium.get('%s%s' % (web_url, '/')) wait = WebDriverWait(selenium, 60) # Click Login Button wait.until(EC.visibility_of_element_located(LOGIN_BUTTON)) selenium.find_element(*LOGIN_BUTTON).click() # Login Using Auth0 wait.until(EC.visibility_of_element_located(AUTH0_LOCK_LOGIN_FORM)) selenium.find_element(*AUTH0_LOCK_EMAIL_INPUT).send_keys(user_email) selenium.find_element(*AUTH0_LOCK_PASSWORD_INPUT).send_keys(user_password) selenium.find_element(*AUTH0_LOCK_SUBMIT_BUTTON).click() # TODO: This really should be using some conditional logic! wait.until(EC.visibility_of_element_located(AUTH0_AUTHORIZE_MODAL)) selenium.find_element(*AUTH0_AUTHORIZE_ALLOW_BUTTON).click() # Wait for page to load after returning to the single page app. wait.until(EC.visibility_of_element_located(EXTERNAL_API_PAGE_LINK)) selenium.find_element(*EXTERNAL_API_PAGE_LINK).click() # Wait for the button to appear after clicking on the external api page button. wait.until(EC.visibility_of_element_located(BUTTON_TO_TRIGGER_API_CALL_USING_TOKEN)) selenium.find_element(*BUTTON_TO_TRIGGER_API_CALL_USING_TOKEN).click() # Check the returned data. wait.until(EC.visibility_of_element_located(EXTERNAL_API_CALL_RESULTS)) api_result = selenium.find_element(*EXTERNAL_API_CALL_RESULTS) api_result_text = api_result.text assert '"provider": "auth0"' in api_result_text assert 'user_metadata' in api_result_text

42.108911

120

0.795909

595

4,253

5.260504

0.161345

0.061342

0.097125

0.080511

0.813419

0.78147

0.773163

0.762939

0.731629

0

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false

0.078125

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0

null

0

1

0

null

0

1

0

7

de355b7317691bdf092eb6e47c76f63f640d1878

6,749

py

Python

experiments/predefined/wiki.py

wimurad1981/DS8008-NLP

b344b7e453e8b77e155fefd91c111c6fa2bd3c74

[ "MIT" ]

22

2020-03-24T11:46:49.000Z

2022-02-09T15:55:28.000Z

experiments/predefined/wiki.py

malteos/aspect-document-embeddings

0836ea54a9192dbc2b01bb212c7521668bb398af

[ "MIT" ]

1

2021-03-15T13:50:19.000Z

2021-03-18T17:54:43.000Z

experiments/predefined/wiki.py

malteos/aspect-document-embeddings

0836ea54a9192dbc2b01bb212c7521668bb398af

[ "MIT" ]

2

2020-04-16T02:34:51.000Z

2022-02-15T05:45:40.000Z

# from transformers import AlbertModel, AlbertTokenizer from experiments.predefined import update from experiments.predefined.base_wiki import env, base_config, siamese_config, joint_config, bert_base_config, \ roberta_base_config, xlnet_base_config, seq512_config, seq256_config, seq128_config, seq64_config, concat2d_config, \ concat3d_config, concat4d_config print(f'Data directory: {env["data_dir"]}') #### bert_base__joint__seq512 = update( update( update( base_config.copy(), bert_base_config ), joint_config ), seq512_config ) bert_base__joint__seq256 = update( update( update( base_config.copy(), bert_base_config ), joint_config ), seq256_config ) bert_base__joint__seq128 = update( update( update( base_config.copy(), bert_base_config ), joint_config ), seq128_config ) bert_base__joint__seq64 = update( update( update( base_config.copy(), bert_base_config ), joint_config ), seq64_config ) ## # # roberta_base__joint__seq512 = update( # update( # update( # base_config.copy(), # roberta_base_config # ), # joint_config # ), # seq512_config # ) # # roberta_base__joint__seq256 = update( # update( # update( # base_config.copy(), # roberta_base_config # ), # joint_config # ), # seq256_config # ) # # roberta_base__joint__seq128 = update( # update( # update( # base_config.copy(), # roberta_base_config # ), # joint_config # ), # seq128_config # ) # # roberta_base__joint__seq64 = update( # update( # update( # base_config.copy(), # roberta_base_config # ), # joint_config # ), # seq64_config # ) ## xlnet_base__joint__seq512 = update( update( update( base_config.copy(), xlnet_base_config ), joint_config ), seq512_config ) xlnet_base__joint__seq256 = update( update( update( base_config.copy(), xlnet_base_config ), joint_config ), seq256_config ) xlnet_base__joint__seq128 = update( update( update( base_config.copy(), xlnet_base_config ), joint_config ), seq128_config ) xlnet_base__joint__seq64 = update( update( update( base_config.copy(), xlnet_base_config ), joint_config ), seq64_config ) bert_base__siamese__seq64__2d = update( update(update(update(base_config, bert_base_config), siamese_config), seq64_config), concat2d_config) bert_base__siamese__seq128__2d = update( update(update(update(base_config, bert_base_config), siamese_config), seq128_config), concat2d_config) bert_base__siamese__seq256__2d = update( update(update(update(base_config, bert_base_config), siamese_config), seq256_config), concat2d_config) bert_base__siamese__seq512__2d = update( update(update(update(base_config, bert_base_config), siamese_config), seq512_config), concat2d_config) bert_base__siamese__seq64__3d = update( update(update(update(base_config, bert_base_config), siamese_config), seq64_config), concat3d_config) bert_base__siamese__seq128__3d = update( update(update(update(base_config, bert_base_config), siamese_config), seq128_config), concat3d_config) bert_base__siamese__seq256__3d = update( update(update(update(base_config, bert_base_config), siamese_config), seq256_config), concat3d_config) bert_base__siamese__seq512__3d = update( update(update(update(base_config, bert_base_config), siamese_config), seq512_config), concat3d_config) bert_base__siamese__seq64__4d = update( update(update(update(base_config, bert_base_config), siamese_config), seq64_config), concat4d_config) bert_base__siamese__seq128__4d = update( update(update(update(base_config, bert_base_config), siamese_config), seq128_config), concat4d_config) bert_base__siamese__seq256__4d = update( update(update(update(base_config, bert_base_config), siamese_config), seq256_config), concat4d_config) bert_base__siamese__seq512__4d = update( update(update(update(base_config, bert_base_config), siamese_config), seq512_config), concat4d_config) xlnet_base__siamese__seq64__2d = update( update(update(update(base_config, xlnet_base_config), siamese_config), seq64_config), concat2d_config) xlnet_base__siamese__seq128__2d = update( update(update(update(base_config, xlnet_base_config), siamese_config), seq128_config), concat2d_config) xlnet_base__siamese__seq256__2d = update( update(update(update(base_config, xlnet_base_config), siamese_config), seq256_config), concat2d_config) xlnet_base__siamese__seq512__2d = update( update(update(update(base_config, xlnet_base_config), siamese_config), seq512_config), concat2d_config) xlnet_base__siamese__seq64__3d = update( update(update(update(base_config, xlnet_base_config), siamese_config), seq64_config), concat3d_config) xlnet_base__siamese__seq128__3d = update( update(update(update(base_config, xlnet_base_config), siamese_config), seq128_config), concat3d_config) xlnet_base__siamese__seq256__3d = update( update(update(update(base_config, xlnet_base_config), siamese_config), seq256_config), concat3d_config) xlnet_base__siamese__seq512__3d = update( update(update(update(base_config, xlnet_base_config), siamese_config), seq512_config), concat3d_config) xlnet_base__siamese__seq64__4d = update( update(update(update(base_config, xlnet_base_config), siamese_config), seq64_config), concat4d_config) xlnet_base__siamese__seq128__4d = update( update(update(update(base_config, xlnet_base_config), siamese_config), seq128_config), concat4d_config) xlnet_base__siamese__seq256__4d = update( update(update(update(base_config, xlnet_base_config), siamese_config), seq256_config), concat4d_config) xlnet_base__siamese__seq512__4d = update( update(update(update(base_config, xlnet_base_config), siamese_config), seq512_config), concat4d_config) #### dummy for local dev _dummy = update( update( update( base_config.copy(), bert_base_config ), joint_config ), dict( data_helper_params=dict( # df_limit=10, wiki_articles_path='./output/enwiki-20191101-pages-articles.weighted.100.jsonl', wiki_relations_path='./wiki/relations.csv', ), epochs=0, ) )

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de6d79d03b4abcdcb7ab7b97b754c0e0ccd978f2

15,748

py

Python

obqa/nn/knowledge.py

dianags/OpenBookQA

186dcd4d90633f13706966925995ff0f135ffd11

[ "Apache-2.0" ]

66

2018-10-23T03:55:03.000Z

2021-07-29T07:38:17.000Z

obqa/nn/knowledge.py

dianags/OpenBookQA

186dcd4d90633f13706966925995ff0f135ffd11

[ "Apache-2.0" ]

4

2019-02-19T05:46:16.000Z

2021-06-04T01:17:38.000Z

obqa/nn/knowledge.py

dianags/OpenBookQA

186dcd4d90633f13706966925995ff0f135ffd11

[ "Apache-2.0" ]

23

2018-10-23T22:30:11.000Z

2022-03-11T00:35:48.000Z

from allennlp.nn.util import get_text_field_mask, get_final_encoder_states from typing import Union, Dict import torch from allennlp.modules import MatrixAttention, Seq2SeqEncoder from obqa.nn.util import seq2vec_seq_aggregate def attention_combinations_dict(quest_repr_list, choices_repr_list, inter_to_include, att_matrix_mappings: Union[MatrixAttention, Dict[str, MatrixAttention]]): """ This method calculates interactions between different representations for question and choices. :param quest_repr_list: :param choices_repr_list: :param inter_to_include: :param att_matrix_mappings: :return: """ att_matrix_mappings_dict = {} if isinstance(att_matrix_mappings, MatrixAttention): att_matrix_mappings_dict["default"] = att_matrix_mappings elif isinstance(att_matrix_mappings, dict): att_matrix_mappings_dict = att_matrix_mappings else: raise ValueError("att_matrix_mappings should be either MatrixAttention, Dict[str, MatrixAttention]") interactions = [] for inter_setting in inter_to_include: inter_setting_key = "_".join(inter_setting) att_matrix = att_matrix_mappings_dict.get(inter_setting_key, att_matrix_mappings_dict.get("default")) curr_inter = att_matrix(quest_repr_list[inter_setting[0]].unsqueeze(1), choices_repr_list[inter_setting[1]]) \ .squeeze(1) # last squeeze is to fix the question unsqueeze. interactions.append(curr_inter.unsqueeze(-1)) concat_inter = torch.cat(interactions, dim=-1) return concat_inter def attention_interaction_combinations(quest_ctx, choices_ctx, quest_ctx_plus_kn, choices_ctx_plus_kn, quest_kn, choices_kn, inter_to_include, att_matrix_mappings: Union[MatrixAttention, Dict[str, MatrixAttention]]): """ This method calculates interactions between different representations for question and choices. Currently it is not optimized! Calculated sequentially for type tuples [("ctx", "ctx+kn"), ("ctx+kn", "ctx"), etc.] :param quest_ctx: :param choices_ctx: :param quest_ctx_plus_kn: :param choices_ctx_plus_kn: :param quest_kn: :param choices_kn: :param inter_to_include: :return: Interactions combinations """ quest_repr_list = { "ctx": quest_ctx, "ctx+kn": quest_ctx_plus_kn, "kn": quest_kn, } choices_repr_list = { "ctx": choices_ctx, "ctx+kn": choices_ctx_plus_kn, "kn": choices_kn, } att_matrix_mappings_dict = {} if isinstance(att_matrix_mappings, MatrixAttention): att_matrix_mappings_dict["default"] = att_matrix_mappings elif isinstance(att_matrix_mappings, dict): att_matrix_mappings_dict = att_matrix_mappings else: raise ValueError("att_matrix_mappings should be either MatrixAttention, Dict[str, MatrixAttention]") interactions = [] for inter_setting in inter_to_include: inter_setting_key = "_".join(inter_setting) att_matrix = att_matrix_mappings_dict.get(inter_setting_key, att_matrix_mappings_dict.get("default")) curr_inter = att_matrix(quest_repr_list[inter_setting[0]].unsqueeze(1), choices_repr_list[inter_setting[1]]) \ .squeeze(1) # last squeeze is to fix the question unsqueeze. interactions.append(curr_inter.unsqueeze(-1)) concat_inter = torch.cat(interactions, dim=-1) return concat_inter def embedd_encode_and_aggregate_text_field(question: Dict[str, torch.LongTensor], text_field_embedder, embeddings_dropout, encoder, aggregation_type, get_last_states=False): embedded_question = text_field_embedder(question) question_mask = get_text_field_mask(question).float() embedded_question = embeddings_dropout(embedded_question) encoded_question = encoder(embedded_question, question_mask) # aggregate sequences to a single item encoded_question_aggregated = seq2vec_seq_aggregate(encoded_question, question_mask, aggregation_type, encoder.is_bidirectional(), 1) # bs X d last_hidden_states = None if get_last_states: last_hidden_states = get_final_encoder_states(encoded_question, question_mask, encoder.is_bidirectional()) return encoded_question_aggregated, last_hidden_states def embedd_encode_and_aggregate_list_text_field(texts_list: Dict[str, torch.LongTensor], text_field_embedder, embeddings_dropout, encoder: Seq2SeqEncoder, aggregation_type, init_hidden_states=None): embedded_texts = text_field_embedder(texts_list) embedded_texts = embeddings_dropout(embedded_texts) bs, ch_cnt, ch_tkn_cnt, d = tuple(embedded_texts.shape) embedded_texts_flattened = embedded_texts.view([bs * ch_cnt, ch_tkn_cnt, -1]) # masks texts_mask_dim_3 = get_text_field_mask(texts_list, num_wrapping_dims=1).float() texts_mask_flatened = texts_mask_dim_3.view([-1, ch_tkn_cnt]) # context encoding multiple_texts_init_states = None if init_hidden_states is not None: if init_hidden_states.shape[0] == bs and init_hidden_states.shape[1] != ch_cnt: if init_hidden_states.shape[1] != encoder.get_output_dim(): raise ValueError("The shape of init_hidden_states is {0} but is expected to be {1} or {2}".format(str(init_hidden_states.shape), str([bs, encoder.get_output_dim()]), str([bs, ch_cnt, encoder.get_output_dim()]))) # in this case we passed only 2D tensor which is the default output from question encoder multiple_texts_init_states = init_hidden_states.unsqueeze(1).expand([bs, ch_cnt, encoder.get_output_dim()]).contiguous() # reshape this to match the flattedned tokens multiple_texts_init_states = multiple_texts_init_states.view([bs * ch_cnt, encoder.get_output_dim()]) else: multiple_texts_init_states = init_hidden_states.view([bs * ch_cnt, encoder.get_output_dim()]) encoded_texts_flattened = encoder(embedded_texts_flattened, texts_mask_flatened, hidden_state=multiple_texts_init_states) aggregated_choice_flattened = seq2vec_seq_aggregate(encoded_texts_flattened, texts_mask_flatened, aggregation_type, encoder.is_bidirectional(), 1) # bs*ch X d aggregated_choice_flattened_reshaped = aggregated_choice_flattened.view([bs, ch_cnt, -1]) return aggregated_choice_flattened_reshaped def embed_encode_and_aggregate_text_field_with_feats(question: Dict[str, torch.LongTensor], text_field_embedder, embeddings_dropout, encoder, aggregation_type, token_features=None, get_last_states=False): embedded_question = text_field_embedder(question) question_mask = get_text_field_mask(question).float() embedded_question = embeddings_dropout(embedded_question) if token_features is not None: embedded_question = torch.cat([embedded_question, token_features], dim=-1) encoded_question = encoder(embedded_question, question_mask) # aggregate sequences to a single item encoded_question_aggregated = seq2vec_seq_aggregate(encoded_question, question_mask, aggregation_type, encoder.is_bidirectional(), 1) # bs X d last_hidden_states = None if get_last_states: last_hidden_states = get_final_encoder_states(encoded_question, question_mask, encoder.is_bidirectional()) return encoded_question_aggregated, last_hidden_states def embed_encode_and_aggregate_text_field_with_feats_only(question: Dict[str, torch.LongTensor], text_field_embedder, embeddings_dropout, encoder, aggregation_type, token_features=None, get_last_states=False): embedded_question = text_field_embedder(question) question_mask = get_text_field_mask(question).float() embedded_question = embeddings_dropout(embedded_question) if token_features is not None: embedded_question = torch.cat([token_features], dim=-1) encoded_question = encoder(embedded_question, question_mask) # aggregate sequences to a single item encoded_question_aggregated = seq2vec_seq_aggregate(encoded_question, question_mask, aggregation_type, encoder.is_bidirectional(), 1) # bs X d last_hidden_states = None if get_last_states: last_hidden_states = get_final_encoder_states(encoded_question, question_mask, encoder.is_bidirectional()) return encoded_question_aggregated, last_hidden_states def embed_encode_and_aggregate_list_text_field_with_feats(texts_list: Dict[str, torch.LongTensor], text_field_embedder, embeddings_dropout, encoder: Seq2SeqEncoder, aggregation_type, token_features=None, init_hidden_states=None): embedded_texts = text_field_embedder(texts_list) embedded_texts = embeddings_dropout(embedded_texts) if token_features is not None: embedded_texts = torch.cat([embedded_texts, token_features], dim=-1) bs, ch_cnt, ch_tkn_cnt, d = tuple(embedded_texts.shape) embedded_texts_flattened = embedded_texts.view([bs * ch_cnt, ch_tkn_cnt, -1]) # masks texts_mask_dim_3 = get_text_field_mask(texts_list, num_wrapping_dims=1).float() texts_mask_flatened = texts_mask_dim_3.view([-1, ch_tkn_cnt]) # context encoding multiple_texts_init_states = None if init_hidden_states is not None: if init_hidden_states.shape[0] == bs and init_hidden_states.shape[1] != ch_cnt: if init_hidden_states.shape[1] != encoder.get_output_dim(): raise ValueError("The shape of init_hidden_states is {0} but is expected to be {1} or {2}".format(str(init_hidden_states.shape), str([bs, encoder.get_output_dim()]), str([bs, ch_cnt, encoder.get_output_dim()]))) # in this case we passed only 2D tensor which is the default output from question encoder multiple_texts_init_states = init_hidden_states.unsqueeze(1).expand([bs, ch_cnt, encoder.get_output_dim()]).contiguous() # reshape this to match the flattedned tokens multiple_texts_init_states = multiple_texts_init_states.view([bs * ch_cnt, encoder.get_output_dim()]) else: multiple_texts_init_states = init_hidden_states.view([bs * ch_cnt, encoder.get_output_dim()]) encoded_texts_flattened = encoder(embedded_texts_flattened, texts_mask_flatened, hidden_state=multiple_texts_init_states) aggregated_choice_flattened = seq2vec_seq_aggregate(encoded_texts_flattened, texts_mask_flatened, aggregation_type, encoder.is_bidirectional(), 1) # bs*ch X d aggregated_choice_flattened_reshaped = aggregated_choice_flattened.view([bs, ch_cnt, -1]) return aggregated_choice_flattened_reshaped def embed_encode_and_aggregate_list_text_field_with_feats_only(texts_list: Dict[str, torch.LongTensor], text_field_embedder, embeddings_dropout, encoder: Seq2SeqEncoder, aggregation_type, token_features=None, init_hidden_states=None): embedded_texts = text_field_embedder(texts_list) embedded_texts = embeddings_dropout(embedded_texts) if token_features is not None: embedded_texts = torch.cat([token_features], dim=-1) bs, ch_cnt, ch_tkn_cnt, d = tuple(embedded_texts.shape) embedded_texts_flattened = embedded_texts.view([bs * ch_cnt, ch_tkn_cnt, -1]) # masks texts_mask_dim_3 = get_text_field_mask(texts_list, num_wrapping_dims=1).float() texts_mask_flatened = texts_mask_dim_3.view([-1, ch_tkn_cnt]) # context encoding multiple_texts_init_states = None if init_hidden_states is not None: if init_hidden_states.shape[0] == bs and init_hidden_states.shape[1] != ch_cnt: if init_hidden_states.shape[1] != encoder.get_output_dim(): raise ValueError("The shape of init_hidden_states is {0} but is expected to be {1} or {2}".format(str(init_hidden_states.shape), str([bs, encoder.get_output_dim()]), str([bs, ch_cnt, encoder.get_output_dim()]))) # in this case we passed only 2D tensor which is the default output from question encoder multiple_texts_init_states = init_hidden_states.unsqueeze(1).expand([bs, ch_cnt, encoder.get_output_dim()]).contiguous() # reshape this to match the flattedned tokens multiple_texts_init_states = multiple_texts_init_states.view([bs * ch_cnt, encoder.get_output_dim()]) else: multiple_texts_init_states = init_hidden_states.view([bs * ch_cnt, encoder.get_output_dim()]) encoded_texts_flattened = encoder(embedded_texts_flattened, texts_mask_flatened, hidden_state=multiple_texts_init_states) aggregated_choice_flattened = seq2vec_seq_aggregate(encoded_texts_flattened, texts_mask_flatened, aggregation_type, encoder.is_bidirectional(), 1) # bs*ch X d aggregated_choice_flattened_reshaped = aggregated_choice_flattened.view([bs, ch_cnt, -1]) return aggregated_choice_flattened_reshaped

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1

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1

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null

0

7

decaf32be6869ac1ecfa3f63fcefc30e18ea4a6a

117,196

py

Python

tests/test_306_jsondiff.py

SD2E/python-datacatalog

51ab366639505fb6e8a14cd6b446de37080cd20d

[ "CNRI-Python" ]

null

tests/test_306_jsondiff.py

SD2E/python-datacatalog

51ab366639505fb6e8a14cd6b446de37080cd20d

[ "CNRI-Python" ]

2

2019-07-25T15:39:04.000Z

2019-10-21T15:31:46.000Z

tests/test_306_jsondiff.py

SD2E/python-datacatalog

51ab366639505fb6e8a14cd6b446de37080cd20d

[ "CNRI-Python" ]

1

2019-10-15T14:33:44.000Z

import pytest import os import json from datacatalog.linkedstores.basestore.diff import get_diff, diff_list HERE = os.path.dirname(os.path.abspath(__file__)) PARENT = os.path.dirname(HERE) DATA_DIR = os.path.join(HERE, 'data/sampleset') def test_json_diff_mixed_lists(): foo = { 'uuid': 1, 'parameters' : [ { 'recovery_info' : {'recovery_media': 'foo', 'recovery_sample_vol': '100:microliter', 'recovery_media_vol': '400:microliter', 'inc_time_2': '3:hour'}}]} bar = { 'uuid': 1, 'parameters' : [ { 'recovery_info' : [{'recovery_media': 'bar', 'recovery_sample_vol': '100:microliter', 'recovery_media_vol': '400:microliter', 'inc_time_2': '3:hour'}]}]} merge_source = foo merge_dest = bar diff_record = get_diff(source=merge_source, target=merge_dest, action='update') s_updated = diff_record.updated assert json.loads(diff_record.delta) != dict() assert s_updated == True # ensure inverse works merge_source = bar merge_dest = foo diff_record = get_diff(source=merge_source, target=merge_dest, action='update') s_updated = diff_record.updated assert json.loads(diff_record.delta) != dict() assert s_updated == True def test_json_diff_recursion(): # check diff list functions list1 = [] list2 = [] assert diff_list(list1, list2) == [] list1 = ['12757493', '12757494', '12757495'] list2 = ['12757493', '12757494', '12757495'] assert diff_list(list1, list2) == [] list1 = ['12757493', '12757494'] list2 = ['12757493', '12757494', '12757495'] assert diff_list(list1, list2) == ['12757495'] list1 = ['12757493', '12757494', '12757495'] list2 = ['12757493', '12757494'] assert diff_list(list1, list2) == ['12757495'] # cross-type lists merge_source = {'replicate': [1, 2, 3, 4, 5, 6], 'uuid': '10342eae-c840-5c95-ad3b-4dd680a81a0f'} merge_dest = {'replicate': 6, 'uuid': '10342eae-c840-5c95-ad3b-4dd680a81a0f'} diff_record = get_diff(source=merge_source, target=merge_dest, action='update') s_updated = diff_record.updated assert json.loads(diff_record.delta) == {'$update': {'replicate': 6}, 'replicate': 6} assert s_updated == True # flip lists merge_source = {'replicate': 6, 'uuid': '10342eae-c840-5c95-ad3b-4dd680a81a0f'} merge_dest = {'replicate': [1, 2, 3, 4, 5, 6], 'uuid': '10342eae-c840-5c95-ad3b-4dd680a81a0f'} diff_record = get_diff(source=merge_source, target=merge_dest, action='update') s_updated = diff_record.updated assert json.loads(diff_record.delta) == {'$update': {'replicate': [1, 2, 3, 4, 5, 6]}, 'replicate': 6} assert s_updated == True # Not PEP8 friendly. # Example production documents of fluorescein controls from Ginkgo # Short lists - should not trigger issues with recursion # These documents should have no difference merge_source = {'_id': '5cd31bd84c52fafe64357d88', 'sample_id': 'sample.ginkgo.12795734.experiment.ginkgo.19606.19637.19708.19709', 'lab_sample_id': 'sample.ginkgo.12795734', 'contents': [{'name': {'sbh_uri': 'https://hub.sd2e.org/user/sd2e/design/fluorescein/1', 'label': 'Fluorescein', 'lab_id': 'name.ginkgo.445'}, 'value': 6.25e-07, 'unit': 'M'}, {'name': {'sbh_uri': 'https://hub.sd2e.org/user/sd2e/design/pbs/1', 'label': 'Phosphate Buffered Saline', 'lab_id': 'name.ginkgo.20'}, 'value': 1.0, 'unit': 'X'}], 'standard_type': 'FLUORESCEIN', 'uuid': '10342eae-c840-5c95-ad3b-4dd680a81a0f'} merge_dest = {'_id': '5cd31bd84c52fafe64357d88', 'sample_id': 'sample.ginkgo.12795734.experiment.ginkgo.19606.19637.19708.19709', 'lab_sample_id': 'sample.ginkgo.12795734', 'contents': [{'name': {'sbh_uri': 'https://hub.sd2e.org/user/sd2e/design/fluorescein/1', 'label': 'Fluorescein', 'lab_id': 'name.ginkgo.445'}, 'value': 6.25e-07, 'unit': 'M'}, {'name': {'sbh_uri': 'https://hub.sd2e.org/user/sd2e/design/pbs/1', 'label': 'Phosphate Buffered Saline', 'lab_id': 'name.ginkgo.20'}, 'value': 1.0, 'unit': 'X'}], 'standard_type': 'FLUORESCEIN', 'uuid': '10342eae-c840-5c95-ad3b-4dd680a81a0f'} diff_record = get_diff(source=merge_source, target=merge_dest, action='update') s_updated = diff_record.updated assert json.loads(diff_record.delta) == dict() assert s_updated == False # Not PEP8 friendly. # Example production documents of fluorescein controls from Ginkgo # Long lists - will trigger maximum recursion depth exceeded in comparison # These should have no difference merge_source = {'_id': '5cd31bd84c52fafe64357d88', 'sample_id': 'sample.ginkgo.12795734.experiment.ginkgo.19606.19637.19708.19709', 'lab_sample_id': 'sample.ginkgo.12795734', 'contents': [{'name': {'sbh_uri': 'https://hub.sd2e.org/user/sd2e/design/fluorescein/1', 'label': 'Fluorescein', 'lab_id': 'name.ginkgo.445'}, 'value': 6.25e-07, 'unit': 'M'}, {'name': {'sbh_uri': 'https://hub.sd2e.org/user/sd2e/design/pbs/1', 'label': 'Phosphate Buffered Saline', 'lab_id': 'name.ginkgo.20'}, 'value': 1.0, 'unit': 'X'}], 'standard_type': 'FLUORESCEIN', 'standard_for': ['12757493', '12757494', '12757495', '12757496', '12752235', '12753603', '12757498', '12689579', '12689580', '12689581', '12689582', '12689583', '12689584', '12689585', '12689586', '12689587', '12689588', '12689589', '12689590', '12689591', '12689592', '12689593', '12689594', '12689595', '12689596', '12689597', '12689598', '12689599', '12689600', '12689601', '12689602', '12689603', '12689604', '12689605', '12689606', '12689607', '12689608', '12689609', '12689610', '12689611', '12689612', '12689613', '12689614', '12689615', '12689616', '12689617', '12689618', '12689619', '12689620', '12689621', '12689622', '12689623', '12689624', '12689625', '12689626', '12689627', '12689628', '12689629', '12689630', '12689631', '12689632', '12689633', '12689634', '12689635', '12689636', '12689637', '12689638', '12753621', '12753627', '12752265', '12753633', '12753639', '12753645', '12753651', '12722615', '12722616', '12722617', '12722618', '12722619', '12722620', '12722621', '12722622', '12722623', '12722624', '12722625', '12722626', '12722627', '12722628', '12722629', '12722630', '12722631', '12722632', '12722633', '12722634', '12722635', '12722636', '12722637', '12722638', '12722639', '12722640', '12722641', '12722642', '12722643', '12722644', '12722645', '12722646', '12722647', '12722648', '12722649', '12722650', '12722651', '12722652', '12722653', '12722654', '12722655', '12722656', '12722657', '12722658', '12722659', '12722660', '12722661', '12722662', '12722663', '12722664', '12722665', '12722666', '12722667', '12722668', '12722669', '12722670', '12722671', '12722672', '12722673', '12722674', '12752325', '12752355', '12752385', '12757444', '12748420', '12748421', '12748422', '12748423', '12748424', '12748425', '12748426', '12748427', '12748428', '12748429', '12748430', '12748431', '12748432', '12748433', '12748434', '12748435', '12748436', '12748437', '12748438', '12748439', '12748440', '12748441', '12748442', '12748443', '12748444', '12748445', '12748446', '12748447', '12748448', '12748449', '12748450', '12748451', '12748452', '12748453', '12748454', '12748455', '12748456', '12748457', '12748458', '12748459', '12748460', '12748461', '12748462', '12748463', '12748464', '12748465', '12748466', '12748467', '12748468', '12748469', '12748470', '12748471', '12748472', '12748473', '12748474', '12748475', '12748476', '12748477', '12748478', '12748479', '12757476', '12757477', '12756884', '12756885', '12756886', '12756887', '12756888', '12756889', '12756890', '12756891', '12756892', '12756893', '12756894', '12756895', '12756896', '12756897', '12756898', '12756899', '12756900', '12756901', '12756902', '12756903', '12756904', '12756905', '12756906', '12756907', '12756908', '12756909', '12756910', '12756911', '12756912', '12756913', '12756914', '12756915', '12756916', '12756917', '12756918', '12756919', '12756920', '12756921', '12756922', '12756923', '12756924', '12756925', '12756926', '12756927', '12756928', '12756929', '12756930', '12756931', '12756932', '12756933', '12756934', '12756935', '12756936', '12756937', '12756938', '12756939', '12756940', '12756941', '12756942', '12756943', '12752295', '12757425', '12675395', '12675396', '12675397', '12675398', '12675399', '12675400', '12675401', '12675402', '12675403', '12675404', '12675405', '12675406', '12675407', '12675408', '12675409', '12675410', '12675411', '12675412', '12675413', '12675414', '12675415', '12675416', '12675417', '12675418', '12675419', '12675420', '12675421', '12675422', '12675423', '12675424', '12675425', '12675426', '12675427', '12675428', '12675429', '12675430', '12675431', '12675432', '12675433', '12675434', '12675435', '12675436', '12675437', '12675438', '12675439', '12675440', '12675441', '12675442', '12675443', '12675444', '12675445', '12675446', '12675447', '12675448', '12675449', '12675450', '12675451', '12675452', '12675453', '12675454', '12675455', '12675456', '12675457', '12675458', '12675459', '12675460', '12675461', '12675462', '12675463', '12675464', '12675465', '12675466', '12675467', '12675468', '12675469', '12675470', '12675471', '12675472', '12675473', '12675474', '12675475', '12675476', '12675477', '12675478', '12675479', '12675480', '12675481', '12675482', '12675483', '12675484', '12675485', '12675486', '12675487', '12675488', '12675489', '12675490', '12675491', '12675492', '12675493', '12675494', '12675495', '12675496', '12675497', '12675498', '12675499', '12675500', '12675501', '12675502', '12675503', '12675504', '12675505', '12675506', '12675507', '12675508', '12675509', '12675510', '12675511', '12675512', '12675513', '12675514', '12675515', '12675516', '12675517', '12675518', '12675519', '12675520', '12675521', '12675522', '12675523', '12675524', '12675525', '12675526', '12675527', '12675528', '12675529', '12675530', '12675531', '12675532', '12675533', '12675534', '12675535', '12675536', '12675537', '12675538', '12675539', '12675540', '12675541', '12675542', '12675543', '12675544', '12675545', '12675546', '12675547', '12675548', '12675549', '12675550', '12675551', '12675552', '12675553', '12675554', '12675555', '12675556', '12675557', '12675558', '12675559', '12675560', '12675561', '12675562', '12675563', '12675564', '12675565', '12675566', '12675567', '12675568', '12675569', '12675570', '12675571', '12675572', '12675573', '12675574', '12675575', '12675576', '12675577', '12675578', '12675579', '12675580', '12675581', '12675582', '12675583', '12675584', '12675585', '12675586', '12675587', '12675588', '12675589', '12675590', '12675591', '12675592', '12675593', '12675594', '12675595', '12675596', '12675597', '12675598', '12675599', '12675600', '12675601', '12675602', '12675603', '12675604', '12675605', '12675606', '12675607', '12675608', '12675609', '12675610', '12675611', '12675612', '12675613', '12675614', '12675615', '12675616', '12675617', '12675618', '12675619', '12675620', '12675621', '12675622', '12675623', '12675624', '12675625', '12675626', '12675627', '12675628', '12675629', '12675630', '12675631', '12675632', '12675633', '12675634', '12757555', '12757556', '12757557', '12757558', '12757559', '12757489', '12757561', '12757562', '12757563', '12757564', '12757565', '12757566', '12757567', '12757568', '12757569', '12757570', '12757571', '12757572', '12757573', '12757574', '12757575', '12757576', '12757577', '12757578', '12757579', '12757580', '12757581', '12757582', '12757583', '12757584', '12757585', '12757586', '12757587', '12757588', '12757589', '12757590', '12757591', '12757592', '12757593', '12757594', '12757595', '12757596', '12757597', '12757598', '12757599', '12757600', '12757601', '12757602', '12757603', '12757604', '12757605', '12757606', '12757607', '12757608', '12757609', '12757610', '12757611', '12757612', '12757613', '12757614', '12757615', '12757482', '12757617', '12757618', '12757619', '12757620', '12757621', '12757622', '12757623', '12757624', '12757625', '12757626', '12757627', '12757628', '12757629', '12757630', '12757631', '12757632', '12757633', '12757634', '12757635', '12757636', '12757637', '12757638', '12757639', '12757640', '12757641', '12757642', '12757643', '12757644', '12757645', '12757646', '12757647', '12757648', '12757649', '12757650', '12757651', '12757652', '12757653', '12757654', '12757655', '12757656', '12757657', '12757658', '12757659', '12757660', '12757661', '12757662', '12757663', '12757664', '12757428', '12757483', '12757429', '12757447', '12757435', '12757430', '12757446', '12757485', '12757431', '12757486', '12757432', '12757490', '12757487', '12757433', '12757488', '12757434', '12757436', '12757491', '12757437', '12752175', '12757438', '12757443', '12757439', '12752184', '12757426', '12757440', '12757441', '12757442', '12752205', '12757497', '12757427', '12757445', '12752160', '12752161', '12752162', '12752163', '12752164', '12752165', '12752166', '12752167', '12752168', '12752169', '12752170', '12752171', '12752172', '12752173', '12752174', '12752176', '12752177', '12752178', '12752179', '12752180', '12752181', '12752182', '12752183', '12752185', '12752186', '12752187', '12752188', '12752189', '12752190', '12752191', '12752192', '12752193', '12752194', '12752195', '12752196', '12752197', '12752198', '12752199', '12752200', '12752201', '12752202', '12752203', '12752204', '12752206', '12752207', '12752208', '12752209', '12752210', '12752211', '12752212', '12752213', '12752214', '12752215', '12752216', '12752217', '12752218', '12752219', '12752220', '12752221', '12752222', '12752223', '12752224', '12752225', '12752226', '12752227', '12752228', '12752229', '12752230', '12752231', '12752232', '12752233', '12752234', '12752236', '12752237', '12752238', '12752239', '12752240', '12752241', '12752242', '12752243', '12752244', '12752245', '12752246', '12752247', '12752248', '12752249', '12752250', '12752251', '12752252', '12752253', '12752254', '12752255', '12752256', '12752257', '12752258', '12752259', '12752260', '12752261', '12752262', '12752263', '12752264', '12752266', '12752267', '12752268', '12752269', '12752270', '12752271', '12752272', '12752273', '12752274', '12752275', '12752276', '12752277', '12752278', '12752279', '12752280', '12752281', '12752282', '12752283', '12752284', '12752285', '12752286', '12752287', '12752288', '12752289', '12752290', '12752291', '12752292', '12752293', '12752294', '12752296', '12752297', '12752298', '12752299', '12752300', '12752301', '12752302', '12752303', '12752304', '12752305', '12752306', '12752307', '12752308', '12752309', '12752310', '12752311', '12752312', '12752313', '12752314', '12752315', '12752316', '12752317', '12752318', '12752319', '12752320', '12752321', '12752322', '12752323', '12752324', '12752326', '12752327', '12752328', '12752329', '12752330', '12752331', '12752332', '12752333', '12752334', '12752335', '12752336', '12752337', '12752338', '12752339', '12752340', '12752341', '12752342', '12752343', '12752344', '12752345', '12752346', '12752347', '12752348', '12752349', '12752350', '12752351', '12752352', '12752353', '12752354', '12752356', '12752357', '12752358', '12752359', '12752360', '12752361', '12752362', '12752363', '12752364', '12752365', '12752366', '12752367', '12752368', '12752369', '12752370', '12752371', '12752372', '12752373', '12752374', '12752375', '12752376', '12752377', '12752378', '12752379', '12752380', '12752381', '12752382', '12752383', '12752384', '12752386', '12752387', '12752388', '12752389', '12752390', '12752391', '12752392', '12752393', '12752394', '12752395', '12752396', '12752397', '12752398', '12752399', '12757448', '12757449', '12753609', '12695693', '12695694', '12695695', '12695696', '12695697', '12695698', '12695699', '12695700', '12695701', '12695702', '12695703', '12695704', '12695705', '12695706', '12695707', '12695708', '12695709', '12695710', '12695711', '12695712', '12695713', '12695714', '12695715', '12695716', '12695717', '12695718', '12695719', '12695720', '12695721', '12695722', '12695723', '12695724', '12695725', '12695726', '12695727', '12695728', '12695729', '12695730', '12695731', '12695732', '12695733', '12695734', '12695735', '12695736', '12695737', '12695738', '12695739', '12695740', '12695741', '12695742', '12695743', '12695744', '12695745', '12695746', '12695747', '12695748', '12695749', '12695750', '12695751', '12695752', '12753615', '12753598', '12753599', '12753600', '12753601', '12753602', '12753604', '12753605', '12753606', '12753607', '12753608', '12753610', '12753611', '12753612', '12753613', '12753614', '12753616', '12753617', '12753618', '12753619', '12753620', '12753622', '12753623', '12753624', '12753625', '12753626', '12753628', '12753629', '12753630', '12753631', '12753632', '12753634', '12753635', '12753636', '12753637', '12753638', '12753640', '12753641', '12753642', '12753643', '12753644', '12753646', '12753647', '12753648', '12753649', '12753650', '12753652', '12753653', '12753654', '12753655', '12753656', '12757450', '12757451', '12757452', '12664632', '12705593', '12757453', '12705594', '12705595', '12664636', '12664637', '12664638', '12757454', '12664639', '12664640', '12664641', '12664642', '12664643', '12757455', '12664644', '12664645', '12664646', '12664647', '12705608', '12757456', 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'12664652', '12664653', '12757457', '12664654', '12664655', '12664656', '12757499', '12664657', '12757500', '12664658', '12757501', '12757458', '12664659', '12757502', '12757503', '12757504', '12757505', '12757506', '12757459', '12664664', '12757507', '12664665', '12757508', '12664666', '12757509', '12664667', '12757510', '12664668', '12757511', '12757460', '12664669', '12757512', '12664670', '12757513', '12664671', '12757514', '12664672', '12757515', '12664673', '12757516', '12757461', '12664674', '12757517', '12664675', '12757518', '12664676', '12757519', '12664677', '12757520', '12664678', '12757521', '12757462', '12664679', '12757522', '12664680', '12757523', '12664681', '12757524', '12664682', '12757525', '12664683', '12757526', '12757463', '12664684', '12757527', '12664685', '12757528', '12664686', '12757529', '12664687', '12757530', '12664688', '12757531', '12757464', '12664689', '12757532', '12664690', '12757533', '12664691', '12757534', '12757535', '12757536', '12757465', '12757537', '12757538', '12757539', '12757540', '12757541', '12757466', '12757542', '12757543', '12757544', '12757545', '12757546', '12757467', '12757547', '12757548', '12757549', '12757550', '12757551', '12757468', '12757552', '12757553', '12757554', '12757469', '12757560', '12757470', '12757471', '12757472', '12757473', '12757474', '12757475', '12753657', '12705292', '12705293', '12705294', '12705295', '12705296', '12705297', '12705298', '12705299', '12705300', '12705301', '12705302', '12705303', '12705304', '12705305', '12705306', '12705307', '12705308', '12705309', '12705310', '12705311', '12705312', '12705313', '12705314', '12705315', '12705316', '12705317', '12705318', '12705319', '12705320', '12705321', '12705322', '12705323', '12705324', '12705325', '12705326', '12705327', '12705328', '12705329', '12705330', '12705331', '12705332', '12705333', '12705334', '12705335', '12705336', '12705337', '12705338', '12705339', '12705340', '12705341', '12705342', '12705343', '12705344', '12705345', '12705346', '12705347', '12705348', '12705349', '12705350', '12705351', '12757478', '12757479', '12757480', '12757616', '12757481', '12705472', '12705473', '12705474', '12705475', '12705476', '12705477', '12705478', '12705479', '12705480', '12705481', '12705482', '12705483', '12705484', '12705485', '12705486', '12705487', '12705488', '12705489', '12705490', '12705491', '12705492', '12705493', '12705494', '12705495', '12705496', '12705497', '12705498', '12705499', '12705500', '12705501', '12705502', '12705503', '12705504', '12705505', '12705506', '12705507', '12705508', '12705509', '12705510', '12705511', '12705512', '12705513', '12705514', '12705515', '12705516', '12705517', '12705518', '12705519', '12705520', '12705521', '12705522', '12705523', '12705524', '12705525', '12705526', '12705527', '12705528', '12705529', '12705530', '12705531', '12757484', '12664600', '12664601', '12664602', '12664603', '12664604', '12664605', '12664606', '12664607', '12664608', '12664609', '12664610', '12664611', '12664612', '12664613', '12664614', '12664615', '12664616', '12664617', '12664618', '12664619', '12664620', '12664621', '12664622', '12664623', '12664624', '12664625', '12664626', '12664627', '12664628', '12664629', '12664630', '12664631', '12705592', '12664633', '12664634', '12664635', '12705596', '12705597', '12705598', '12705599', '12705600', '12705601', '12705602', '12705603', '12705604', '12705605', '12705606', '12705607', '12664648', '12705609', '12705610', '12705611', '12705612', '12705613', '12705614', '12705615', '12705616', '12705617', '12705618', '12705619', '12705620', '12705621', '12705622', '12705623', '12705624', '12705625', '12705626', '12705627', '12705628', '12705629', '12705630', '12705631', '12705632', '12705633', '12705634', '12705635', '12705636', '12705637', '12705638', '12705639', '12705640', '12705641', '12705642', '12705643', '12705644', '12705645', '12705646', '12705647', '12705648', '12705649', '12705650', '12705651', '12664692', '12664693', '12664694', '12664695', '12664696', '12664697', '12664698', '12664699', '12664700', '12664701', '12664702', '12664703', '12664704', '12664705', '12664706', '12664707', '12664708', '12664709', '12664710', '12664711', '12664712', '12664713', '12664714', '12664715', '12664716', '12664717', '12664718', '12664719', '12664720', '12664721', '12664722', '12664723', '12705712', '12705713', '12705714', '12705715', '12705716', '12705717', '12705718', '12705719', '12705720', '12705721', '12705722', '12705723', '12705724', '12705725', '12705726', '12705727', '12705728', '12705729', '12705730', '12705731', '12705732', '12705733', '12705734', '12705735', '12705736', '12705737', '12705738', '12705739', '12705740', '12705741', '12705742', '12705743', '12705744', '12705745', '12705746', '12705747', '12705748', '12705749', '12705750', '12705751', '12705752', '12705753', '12705754', '12705755', '12705756', '12705757', '12705758', '12705759', '12705760', '12705761', '12705762', '12705763', '12705764', '12705765', '12705766', '12705767', '12705768', '12705769', '12705770', '12705771', '12757492'], 'uuid': '10342eae-c840-5c95-ad3b-4dd680a81a0f'} diff_record = get_diff(source=merge_source, target=merge_dest, action='update') s_updated = diff_record.updated assert json.loads(diff_record.delta) == dict() assert s_updated == False # These should have a minor difference (12757492) at the end of their standard_for_list merge_source = {'_id': '5cd31bd84c52fafe64357d88', 'sample_id': 'sample.ginkgo.12795734.experiment.ginkgo.19606.19637.19708.19709', 'lab_sample_id': 'sample.ginkgo.12795734', 'contents': [{'name': {'sbh_uri': 'https://hub.sd2e.org/user/sd2e/design/fluorescein/1', 'label': 'Fluorescein', 'lab_id': 'name.ginkgo.445'}, 'value': 6.25e-07, 'unit': 'M'}, {'name': {'sbh_uri': 'https://hub.sd2e.org/user/sd2e/design/pbs/1', 'label': 'Phosphate Buffered Saline', 'lab_id': 'name.ginkgo.20'}, 'value': 1.0, 'unit': 'X'}], 'standard_type': 'FLUORESCEIN', 'standard_for': ['12757493', '12757494', '12757495', '12757496', '12752235', '12753603', '12757498', '12689579', '12689580', '12689581', '12689582', '12689583', '12689584', '12689585', '12689586', '12689587', '12689588', '12689589', '12689590', '12689591', '12689592', '12689593', '12689594', '12689595', '12689596', '12689597', '12689598', '12689599', '12689600', '12689601', '12689602', '12689603', '12689604', '12689605', '12689606', '12689607', '12689608', '12689609', '12689610', '12689611', '12689612', '12689613', '12689614', '12689615', '12689616', '12689617', '12689618', '12689619', '12689620', '12689621', '12689622', '12689623', '12689624', '12689625', '12689626', '12689627', '12689628', '12689629', '12689630', '12689631', '12689632', '12689633', '12689634', '12689635', '12689636', '12689637', '12689638', '12753621', '12753627', '12752265', '12753633', '12753639', '12753645', '12753651', '12722615', '12722616', '12722617', '12722618', '12722619', '12722620', '12722621', '12722622', '12722623', 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'12752185', '12752186', '12752187', '12752188', '12752189', '12752190', '12752191', '12752192', '12752193', '12752194', '12752195', '12752196', '12752197', '12752198', '12752199', '12752200', '12752201', '12752202', '12752203', '12752204', '12752206', '12752207', '12752208', '12752209', '12752210', '12752211', '12752212', '12752213', '12752214', '12752215', '12752216', '12752217', '12752218', '12752219', '12752220', '12752221', '12752222', '12752223', '12752224', '12752225', '12752226', '12752227', '12752228', '12752229', '12752230', '12752231', '12752232', '12752233', '12752234', '12752236', '12752237', '12752238', '12752239', '12752240', '12752241', '12752242', '12752243', '12752244', '12752245', '12752246', '12752247', '12752248', '12752249', '12752250', '12752251', '12752252', '12752253', '12752254', '12752255', '12752256', '12752257', '12752258', '12752259', '12752260', '12752261', '12752262', '12752263', '12752264', '12752266', '12752267', '12752268', '12752269', '12752270', '12752271', '12752272', '12752273', '12752274', '12752275', '12752276', '12752277', '12752278', '12752279', '12752280', '12752281', '12752282', '12752283', '12752284', '12752285', '12752286', '12752287', '12752288', '12752289', '12752290', '12752291', '12752292', '12752293', '12752294', '12752296', '12752297', '12752298', '12752299', '12752300', '12752301', '12752302', '12752303', '12752304', '12752305', '12752306', '12752307', '12752308', '12752309', '12752310', '12752311', '12752312', '12752313', '12752314', '12752315', '12752316', '12752317', '12752318', '12752319', '12752320', '12752321', '12752322', '12752323', '12752324', '12752326', '12752327', '12752328', '12752329', '12752330', '12752331', '12752332', '12752333', '12752334', '12752335', '12752336', '12752337', '12752338', '12752339', '12752340', '12752341', '12752342', '12752343', '12752344', '12752345', '12752346', '12752347', '12752348', '12752349', '12752350', '12752351', '12752352', '12752353', '12752354', '12752356', '12752357', '12752358', '12752359', '12752360', '12752361', '12752362', '12752363', '12752364', '12752365', '12752366', '12752367', '12752368', '12752369', '12752370', '12752371', '12752372', '12752373', '12752374', '12752375', '12752376', '12752377', '12752378', '12752379', '12752380', '12752381', '12752382', '12752383', '12752384', '12752386', '12752387', '12752388', '12752389', '12752390', '12752391', '12752392', '12752393', '12752394', '12752395', '12752396', '12752397', '12752398', '12752399', '12757448', '12757449', '12753609', '12695693', '12695694', '12695695', '12695696', '12695697', '12695698', '12695699', '12695700', '12695701', '12695702', '12695703', '12695704', '12695705', '12695706', '12695707', '12695708', '12695709', '12695710', '12695711', '12695712', '12695713', '12695714', '12695715', '12695716', '12695717', '12695718', '12695719', '12695720', '12695721', '12695722', '12695723', '12695724', '12695725', '12695726', '12695727', '12695728', '12695729', '12695730', '12695731', '12695732', '12695733', '12695734', '12695735', '12695736', '12695737', '12695738', '12695739', '12695740', '12695741', '12695742', '12695743', '12695744', '12695745', '12695746', '12695747', '12695748', '12695749', '12695750', '12695751', '12695752', '12753615', '12753598', '12753599', '12753600', '12753601', '12753602', '12753604', '12753605', '12753606', '12753607', '12753608', '12753610', '12753611', '12753612', '12753613', '12753614', '12753616', '12753617', '12753618', '12753619', '12753620', '12753622', '12753623', '12753624', '12753625', '12753626', '12753628', '12753629', '12753630', '12753631', '12753632', '12753634', '12753635', '12753636', '12753637', '12753638', '12753640', '12753641', '12753642', '12753643', '12753644', '12753646', '12753647', '12753648', '12753649', '12753650', '12753652', '12753653', '12753654', '12753655', '12753656', '12757450', '12757451', '12757452', '12664632', '12705593', '12757453', '12705594', '12705595', '12664636', '12664637', '12664638', '12757454', '12664639', '12664640', '12664641', '12664642', '12664643', '12757455', '12664644', '12664645', '12664646', '12664647', '12705608', '12757456', '12664649', '12664650', '12664651', '12664652', '12664653', '12757457', '12664654', '12664655', '12664656', '12757499', '12664657', '12757500', '12664658', '12757501', '12757458', '12664659', '12757502', '12757503', '12757504', '12757505', '12757506', '12757459', '12664664', '12757507', '12664665', '12757508', '12664666', '12757509', '12664667', '12757510', '12664668', '12757511', '12757460', '12664669', '12757512', '12664670', '12757513', '12664671', '12757514', '12664672', '12757515', '12664673', '12757516', '12757461', '12664674', '12757517', '12664675', '12757518', '12664676', '12757519', '12664677', '12757520', '12664678', '12757521', '12757462', '12664679', '12757522', '12664680', '12757523', '12664681', '12757524', '12664682', '12757525', '12664683', '12757526', '12757463', '12664684', '12757527', '12664685', '12757528', '12664686', '12757529', '12664687', '12757530', '12664688', '12757531', '12757464', '12664689', '12757532', '12664690', '12757533', '12664691', '12757534', '12757535', '12757536', '12757465', '12757537', '12757538', '12757539', '12757540', '12757541', '12757466', '12757542', '12757543', '12757544', '12757545', '12757546', '12757467', '12757547', '12757548', '12757549', '12757550', '12757551', '12757468', '12757552', '12757553', '12757554', '12757469', '12757560', '12757470', '12757471', '12757472', '12757473', '12757474', '12757475', '12753657', '12705292', '12705293', '12705294', '12705295', '12705296', '12705297', '12705298', '12705299', '12705300', '12705301', '12705302', '12705303', '12705304', '12705305', '12705306', '12705307', '12705308', '12705309', '12705310', '12705311', '12705312', '12705313', '12705314', '12705315', '12705316', '12705317', '12705318', '12705319', '12705320', '12705321', '12705322', '12705323', '12705324', '12705325', '12705326', '12705327', '12705328', '12705329', '12705330', '12705331', '12705332', '12705333', '12705334', '12705335', '12705336', '12705337', '12705338', '12705339', '12705340', '12705341', '12705342', '12705343', '12705344', '12705345', '12705346', '12705347', '12705348', '12705349', '12705350', '12705351', '12757478', '12757479', '12757480', '12757616', '12757481', '12705472', '12705473', '12705474', '12705475', '12705476', '12705477', '12705478', '12705479', '12705480', '12705481', '12705482', '12705483', '12705484', '12705485', '12705486', '12705487', '12705488', '12705489', '12705490', '12705491', '12705492', '12705493', '12705494', '12705495', '12705496', '12705497', '12705498', '12705499', '12705500', '12705501', '12705502', '12705503', '12705504', '12705505', '12705506', '12705507', '12705508', '12705509', '12705510', '12705511', '12705512', '12705513', '12705514', '12705515', '12705516', '12705517', '12705518', '12705519', '12705520', '12705521', '12705522', '12705523', '12705524', '12705525', '12705526', '12705527', '12705528', '12705529', '12705530', '12705531', '12757484', '12664600', '12664601', '12664602', '12664603', '12664604', '12664605', '12664606', '12664607', '12664608', '12664609', '12664610', '12664611', '12664612', '12664613', '12664614', '12664615', '12664616', '12664617', '12664618', '12664619', '12664620', '12664621', '12664622', '12664623', '12664624', '12664625', '12664626', '12664627', '12664628', '12664629', '12664630', '12664631', '12705592', '12664633', '12664634', '12664635', '12705596', '12705597', '12705598', '12705599', '12705600', '12705601', '12705602', '12705603', '12705604', '12705605', '12705606', '12705607', '12664648', '12705609', '12705610', '12705611', '12705612', '12705613', '12705614', '12705615', '12705616', '12705617', '12705618', '12705619', '12705620', '12705621', '12705622', '12705623', '12705624', '12705625', '12705626', '12705627', '12705628', '12705629', '12705630', '12705631', '12705632', '12705633', '12705634', '12705635', '12705636', '12705637', '12705638', '12705639', '12705640', '12705641', '12705642', '12705643', '12705644', '12705645', '12705646', '12705647', '12705648', '12705649', '12705650', '12705651', '12664692', '12664693', '12664694', '12664695', '12664696', '12664697', '12664698', '12664699', '12664700', '12664701', '12664702', '12664703', '12664704', '12664705', '12664706', '12664707', '12664708', '12664709', '12664710', '12664711', '12664712', '12664713', '12664714', '12664715', '12664716', '12664717', '12664718', '12664719', '12664720', '12664721', '12664722', '12664723', '12705712', '12705713', '12705714', '12705715', '12705716', '12705717', '12705718', '12705719', '12705720', '12705721', '12705722', '12705723', '12705724', '12705725', '12705726', '12705727', '12705728', '12705729', '12705730', '12705731', '12705732', '12705733', '12705734', '12705735', '12705736', '12705737', '12705738', '12705739', '12705740', '12705741', '12705742', '12705743', '12705744', '12705745', '12705746', '12705747', '12705748', '12705749', '12705750', '12705751', '12705752', '12705753', '12705754', '12705755', '12705756', '12705757', '12705758', '12705759', '12705760', '12705761', '12705762', '12705763', '12705764', '12705765', '12705766', '12705767', '12705768', '12705769', '12705770', '12705771'], 'uuid': '10342eae-c840-5c95-ad3b-4dd680a81a0f'} diff_record = get_diff(source=merge_source, target=merge_dest, action='update') s_updated = diff_record.updated assert json.loads(diff_record.delta) == {"standard_for": ["12757492"]} assert s_updated == True # Flipped merged_source and merge_dest above merge_source = {'_id': '5cd31bd84c52fafe64357d88', 'sample_id': 'sample.ginkgo.12795734.experiment.ginkgo.19606.19637.19708.19709', 'lab_sample_id': 'sample.ginkgo.12795734', 'contents': [{'name': {'sbh_uri': 'https://hub.sd2e.org/user/sd2e/design/fluorescein/1', 'label': 'Fluorescein', 'lab_id': 'name.ginkgo.445'}, 'value': 6.25e-07, 'unit': 'M'}, {'name': {'sbh_uri': 'https://hub.sd2e.org/user/sd2e/design/pbs/1', 'label': 'Phosphate Buffered Saline', 'lab_id': 'name.ginkgo.20'}, 'value': 1.0, 'unit': 'X'}], 'standard_type': 'FLUORESCEIN', 'standard_for': ['12757493', '12757494', '12757495', '12757496', '12752235', '12753603', '12757498', '12689579', '12689580', '12689581', '12689582', '12689583', '12689584', '12689585', '12689586', '12689587', '12689588', '12689589', '12689590', '12689591', '12689592', '12689593', '12689594', '12689595', '12689596', '12689597', '12689598', '12689599', '12689600', '12689601', '12689602', '12689603', '12689604', '12689605', '12689606', '12689607', '12689608', '12689609', '12689610', '12689611', '12689612', '12689613', '12689614', '12689615', '12689616', '12689617', '12689618', '12689619', '12689620', '12689621', '12689622', '12689623', '12689624', '12689625', '12689626', '12689627', '12689628', '12689629', '12689630', '12689631', '12689632', '12689633', '12689634', '12689635', '12689636', '12689637', '12689638', '12753621', '12753627', '12752265', '12753633', '12753639', '12753645', '12753651', '12722615', '12722616', '12722617', '12722618', '12722619', '12722620', '12722621', '12722622', '12722623', '12722624', '12722625', '12722626', '12722627', '12722628', '12722629', '12722630', '12722631', '12722632', '12722633', '12722634', '12722635', '12722636', '12722637', '12722638', '12722639', '12722640', '12722641', '12722642', '12722643', '12722644', '12722645', '12722646', '12722647', '12722648', '12722649', '12722650', '12722651', '12722652', '12722653', '12722654', '12722655', '12722656', '12722657', '12722658', '12722659', '12722660', '12722661', '12722662', '12722663', '12722664', '12722665', '12722666', '12722667', '12722668', '12722669', '12722670', '12722671', '12722672', '12722673', '12722674', '12752325', '12752355', '12752385', '12757444', '12748420', '12748421', '12748422', '12748423', '12748424', '12748425', '12748426', '12748427', '12748428', '12748429', '12748430', '12748431', '12748432', '12748433', '12748434', '12748435', '12748436', '12748437', '12748438', '12748439', '12748440', '12748441', '12748442', '12748443', '12748444', '12748445', '12748446', '12748447', '12748448', '12748449', '12748450', '12748451', '12748452', '12748453', '12748454', '12748455', '12748456', '12748457', '12748458', '12748459', '12748460', '12748461', '12748462', '12748463', '12748464', '12748465', '12748466', '12748467', '12748468', '12748469', '12748470', '12748471', '12748472', '12748473', '12748474', '12748475', '12748476', '12748477', '12748478', '12748479', '12757476', '12757477', '12756884', '12756885', '12756886', '12756887', '12756888', '12756889', '12756890', '12756891', '12756892', '12756893', '12756894', '12756895', '12756896', '12756897', '12756898', '12756899', '12756900', '12756901', '12756902', '12756903', '12756904', '12756905', '12756906', '12756907', '12756908', '12756909', '12756910', '12756911', '12756912', '12756913', '12756914', '12756915', '12756916', '12756917', '12756918', '12756919', '12756920', '12756921', '12756922', '12756923', '12756924', '12756925', '12756926', '12756927', '12756928', '12756929', '12756930', '12756931', '12756932', '12756933', '12756934', '12756935', '12756936', '12756937', '12756938', '12756939', '12756940', '12756941', '12756942', '12756943', '12752295', '12757425', '12675395', '12675396', '12675397', '12675398', '12675399', '12675400', '12675401', '12675402', '12675403', '12675404', '12675405', '12675406', '12675407', '12675408', '12675409', '12675410', '12675411', '12675412', '12675413', '12675414', '12675415', '12675416', '12675417', '12675418', '12675419', '12675420', '12675421', '12675422', '12675423', '12675424', '12675425', '12675426', '12675427', '12675428', '12675429', '12675430', '12675431', '12675432', '12675433', '12675434', '12675435', '12675436', '12675437', '12675438', '12675439', '12675440', '12675441', '12675442', '12675443', '12675444', '12675445', '12675446', '12675447', '12675448', 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'12675453', '12675454', '12675455', '12675456', '12675457', '12675458', '12675459', '12675460', '12675461', '12675462', '12675463', '12675464', '12675465', '12675466', '12675467', '12675468', '12675469', '12675470', '12675471', '12675472', '12675473', '12675474', '12675475', '12675476', '12675477', '12675478', '12675479', '12675480', '12675481', '12675482', '12675483', '12675484', '12675485', '12675486', '12675487', '12675488', '12675489', '12675490', '12675491', '12675492', '12675493', '12675494', '12675495', '12675496', '12675497', '12675498', '12675499', '12675500', '12675501', '12675502', '12675503', '12675504', '12675505', '12675506', '12675507', '12675508', '12675509', '12675510', '12675511', '12675512', '12675513', '12675514', '12675515', '12675516', '12675517', '12675518', '12675519', '12675520', '12675521', '12675522', '12675523', '12675524', '12675525', '12675526', '12675527', '12675528', '12675529', '12675530', '12675531', '12675532', '12675533', '12675534', '12675535', '12675536', '12675537', '12675538', '12675539', '12675540', '12675541', '12675542', '12675543', '12675544', '12675545', '12675546', '12675547', '12675548', '12675549', '12675550', '12675551', '12675552', '12675553', '12675554', '12675555', '12675556', '12675557', '12675558', '12675559', '12675560', '12675561', '12675562', '12675563', '12675564', '12675565', '12675566', '12675567', '12675568', '12675569', '12675570', '12675571', '12675572', '12675573', '12675574', '12675575', '12675576', '12675577', '12675578', '12675579', '12675580', '12675581', '12675582', '12675583', '12675584', '12675585', '12675586', '12675587', '12675588', '12675589', '12675590', '12675591', '12675592', '12675593', '12675594', '12675595', '12675596', '12675597', '12675598', '12675599', '12675600', '12675601', '12675602', '12675603', '12675604', '12675605', '12675606', '12675607', '12675608', '12675609', '12675610', '12675611', '12675612', '12675613', '12675614', '12675615', '12675616', '12675617', '12675618', '12675619', '12675620', '12675621', '12675622', '12675623', '12675624', '12675625', '12675626', '12675627', '12675628', '12675629', '12675630', '12675631', '12675632', '12675633', '12675634', '12757555', '12757556', '12757557', '12757558', '12757559', '12757489', '12757561', '12757562', '12757563', '12757564', '12757565', '12757566', '12757567', '12757568', '12757569', '12757570', '12757571', '12757572', '12757573', '12757574', '12757575', '12757576', '12757577', '12757578', '12757579', '12757580', '12757581', '12757582', '12757583', '12757584', '12757585', '12757586', '12757587', '12757588', '12757589', '12757590', '12757591', '12757592', '12757593', '12757594', '12757595', '12757596', '12757597', '12757598', '12757599', '12757600', '12757601', '12757602', '12757603', '12757604', '12757605', '12757606', '12757607', '12757608', '12757609', '12757610', '12757611', '12757612', '12757613', '12757614', '12757615', '12757482', '12757617', '12757618', '12757619', '12757620', '12757621', '12757622', '12757623', '12757624', '12757625', '12757626', '12757627', '12757628', '12757629', '12757630', '12757631', '12757632', '12757633', '12757634', '12757635', '12757636', '12757637', '12757638', '12757639', '12757640', '12757641', '12757642', '12757643', '12757644', '12757645', '12757646', '12757647', '12757648', '12757649', '12757650', '12757651', '12757652', '12757653', '12757654', '12757655', '12757656', '12757657', '12757658', '12757659', '12757660', '12757661', '12757662', '12757663', '12757664', '12757428', '12757483', '12757429', '12757447', '12757435', '12757430', '12757446', '12757485', '12757431', '12757486', '12757432', '12757490', '12757487', '12757433', '12757488', '12757434', '12757436', '12757491', '12757437', '12752175', '12757438', '12757443', '12757439', '12752184', '12757426', '12757440', '12757441', '12757442', '12752205', '12757497', '12757427', '12757445', '12752160', '12752161', '12752162', '12752163', '12752164', '12752165', '12752166', '12752167', '12752168', '12752169', '12752170', '12752171', '12752172', '12752173', '12752174', '12752176', '12752177', '12752178', '12752179', '12752180', '12752181', '12752182', '12752183', '12752185', '12752186', '12752187', '12752188', '12752189', '12752190', '12752191', '12752192', '12752193', '12752194', '12752195', '12752196', '12752197', '12752198', '12752199', '12752200', '12752201', '12752202', '12752203', '12752204', '12752206', '12752207', '12752208', '12752209', '12752210', '12752211', '12752212', '12752213', '12752214', '12752215', '12752216', '12752217', '12752218', '12752219', '12752220', '12752221', '12752222', '12752223', '12752224', '12752225', '12752226', '12752227', '12752228', '12752229', '12752230', '12752231', '12752232', '12752233', '12752234', '12752236', '12752237', '12752238', '12752239', '12752240', '12752241', '12752242', '12752243', '12752244', '12752245', '12752246', '12752247', '12752248', '12752249', '12752250', '12752251', '12752252', '12752253', '12752254', '12752255', '12752256', '12752257', '12752258', '12752259', '12752260', '12752261', '12752262', '12752263', '12752264', '12752266', '12752267', '12752268', '12752269', '12752270', '12752271', '12752272', '12752273', '12752274', '12752275', '12752276', '12752277', '12752278', '12752279', '12752280', '12752281', '12752282', '12752283', '12752284', '12752285', '12752286', '12752287', '12752288', '12752289', '12752290', '12752291', '12752292', '12752293', '12752294', '12752296', '12752297', '12752298', '12752299', '12752300', '12752301', '12752302', '12752303', '12752304', '12752305', '12752306', '12752307', '12752308', '12752309', '12752310', '12752311', '12752312', '12752313', '12752314', '12752315', '12752316', '12752317', '12752318', '12752319', '12752320', '12752321', '12752322', '12752323', '12752324', '12752326', '12752327', '12752328', '12752329', '12752330', '12752331', '12752332', '12752333', '12752334', '12752335', '12752336', '12752337', '12752338', '12752339', '12752340', '12752341', '12752342', '12752343', '12752344', '12752345', '12752346', '12752347', '12752348', '12752349', '12752350', '12752351', '12752352', '12752353', '12752354', '12752356', '12752357', '12752358', '12752359', '12752360', '12752361', '12752362', '12752363', '12752364', '12752365', '12752366', '12752367', '12752368', '12752369', '12752370', '12752371', '12752372', '12752373', '12752374', '12752375', '12752376', '12752377', '12752378', '12752379', '12752380', '12752381', '12752382', '12752383', '12752384', '12752386', '12752387', '12752388', '12752389', '12752390', '12752391', '12752392', '12752393', '12752394', '12752395', '12752396', '12752397', '12752398', '12752399', '12757448', '12757449', '12753609', '12695693', '12695694', '12695695', '12695696', '12695697', '12695698', '12695699', '12695700', '12695701', '12695702', '12695703', '12695704', '12695705', '12695706', '12695707', '12695708', '12695709', '12695710', '12695711', '12695712', '12695713', '12695714', '12695715', '12695716', '12695717', '12695718', '12695719', '12695720', '12695721', '12695722', '12695723', '12695724', '12695725', '12695726', '12695727', '12695728', '12695729', '12695730', '12695731', '12695732', '12695733', '12695734', '12695735', '12695736', '12695737', '12695738', '12695739', '12695740', '12695741', '12695742', '12695743', '12695744', '12695745', '12695746', '12695747', '12695748', '12695749', '12695750', '12695751', '12695752', '12753615', '12753598', '12753599', '12753600', '12753601', '12753602', '12753604', '12753605', '12753606', '12753607', '12753608', '12753610', '12753611', '12753612', '12753613', '12753614', '12753616', '12753617', '12753618', '12753619', '12753620', '12753622', '12753623', '12753624', '12753625', '12753626', '12753628', '12753629', '12753630', '12753631', '12753632', '12753634', '12753635', '12753636', '12753637', '12753638', '12753640', '12753641', '12753642', '12753643', '12753644', '12753646', '12753647', '12753648', '12753649', '12753650', '12753652', '12753653', '12753654', '12753655', '12753656', '12757450', '12757451', '12757452', '12664632', '12705593', '12757453', '12705594', '12705595', '12664636', '12664637', '12664638', '12757454', '12664639', '12664640', '12664641', '12664642', '12664643', '12757455', '12664644', '12664645', '12664646', '12664647', '12705608', '12757456', '12664649', '12664650', '12664651', '12664652', '12664653', '12757457', '12664654', '12664655', '12664656', '12757499', '12664657', '12757500', '12664658', '12757501', '12757458', '12664659', '12757502', '12757503', '12757504', '12757505', '12757506', '12757459', '12664664', '12757507', '12664665', '12757508', '12664666', '12757509', '12664667', '12757510', '12664668', '12757511', '12757460', '12664669', '12757512', '12664670', '12757513', '12664671', '12757514', '12664672', '12757515', '12664673', '12757516', '12757461', '12664674', '12757517', '12664675', '12757518', '12664676', '12757519', '12664677', '12757520', '12664678', '12757521', '12757462', '12664679', '12757522', '12664680', '12757523', '12664681', '12757524', '12664682', '12757525', '12664683', '12757526', '12757463', '12664684', '12757527', '12664685', '12757528', '12664686', '12757529', '12664687', '12757530', '12664688', '12757531', '12757464', '12664689', '12757532', '12664690', '12757533', '12664691', '12757534', '12757535', '12757536', '12757465', '12757537', '12757538', '12757539', '12757540', '12757541', '12757466', '12757542', '12757543', '12757544', '12757545', '12757546', '12757467', '12757547', '12757548', '12757549', '12757550', '12757551', '12757468', '12757552', '12757553', '12757554', '12757469', '12757560', '12757470', '12757471', '12757472', '12757473', '12757474', '12757475', '12753657', '12705292', '12705293', '12705294', '12705295', '12705296', '12705297', '12705298', '12705299', '12705300', '12705301', '12705302', '12705303', '12705304', '12705305', '12705306', '12705307', '12705308', '12705309', '12705310', '12705311', '12705312', '12705313', '12705314', '12705315', '12705316', '12705317', '12705318', '12705319', '12705320', '12705321', '12705322', '12705323', '12705324', '12705325', '12705326', '12705327', '12705328', '12705329', '12705330', '12705331', '12705332', '12705333', '12705334', '12705335', '12705336', '12705337', '12705338', '12705339', '12705340', '12705341', '12705342', '12705343', '12705344', '12705345', '12705346', '12705347', '12705348', '12705349', '12705350', '12705351', '12757478', '12757479', '12757480', '12757616', '12757481', '12705472', '12705473', '12705474', '12705475', '12705476', '12705477', '12705478', '12705479', '12705480', '12705481', '12705482', '12705483', '12705484', '12705485', '12705486', '12705487', '12705488', '12705489', '12705490', '12705491', '12705492', '12705493', '12705494', '12705495', '12705496', '12705497', '12705498', '12705499', '12705500', '12705501', '12705502', '12705503', '12705504', '12705505', '12705506', '12705507', '12705508', '12705509', '12705510', '12705511', '12705512', '12705513', '12705514', '12705515', '12705516', '12705517', '12705518', '12705519', '12705520', '12705521', '12705522', '12705523', '12705524', '12705525', '12705526', '12705527', '12705528', '12705529', '12705530', '12705531', '12757484', '12664600', '12664601', '12664602', '12664603', '12664604', '12664605', '12664606', '12664607', '12664608', '12664609', '12664610', '12664611', '12664612', '12664613', '12664614', '12664615', '12664616', '12664617', '12664618', '12664619', '12664620', '12664621', '12664622', '12664623', '12664624', '12664625', '12664626', '12664627', '12664628', '12664629', '12664630', '12664631', '12705592', '12664633', '12664634', '12664635', '12705596', '12705597', '12705598', '12705599', '12705600', '12705601', '12705602', '12705603', '12705604', '12705605', '12705606', '12705607', '12664648', '12705609', '12705610', '12705611', '12705612', '12705613', '12705614', '12705615', '12705616', '12705617', '12705618', '12705619', '12705620', '12705621', '12705622', '12705623', '12705624', '12705625', '12705626', '12705627', '12705628', '12705629', '12705630', '12705631', '12705632', '12705633', '12705634', '12705635', '12705636', '12705637', '12705638', '12705639', '12705640', '12705641', '12705642', '12705643', '12705644', '12705645', '12705646', '12705647', '12705648', '12705649', '12705650', '12705651', '12664692', '12664693', '12664694', '12664695', '12664696', '12664697', '12664698', '12664699', '12664700', '12664701', '12664702', '12664703', '12664704', '12664705', '12664706', '12664707', '12664708', '12664709', '12664710', '12664711', '12664712', '12664713', '12664714', '12664715', '12664716', '12664717', '12664718', '12664719', '12664720', '12664721', '12664722', '12664723', '12705712', '12705713', '12705714', '12705715', '12705716', '12705717', '12705718', '12705719', '12705720', '12705721', '12705722', '12705723', '12705724', '12705725', '12705726', '12705727', '12705728', '12705729', '12705730', '12705731', '12705732', '12705733', '12705734', '12705735', '12705736', '12705737', '12705738', '12705739', '12705740', '12705741', '12705742', '12705743', '12705744', '12705745', '12705746', '12705747', '12705748', '12705749', '12705750', '12705751', '12705752', '12705753', '12705754', '12705755', '12705756', '12705757', '12705758', '12705759', '12705760', '12705761', '12705762', '12705763', '12705764', '12705765', '12705766', '12705767', '12705768', '12705769', '12705770', '12705771', '12757492'], 'uuid': '10342eae-c840-5c95-ad3b-4dd680a81a0f'} diff_record = get_diff(source=merge_source, target=merge_dest, action='update') s_updated = diff_record.updated assert json.loads(diff_record.delta) == {"standard_for": ["12757492"]} assert s_updated == True # additional use cases testing recursive cases for dictionaries and lists merge_source = { 'uuid': '10342eae-c840-5c95-ad3b-4dd680a81a0f', "k1" : "v1", "k2" : { "k3" : "v3", "k4" : ["v4"] } } merge_dest = { 'uuid': '10342eae-c840-5c95-ad3b-4dd680a81a0f', "k1" : "v1", "k2" : { "k3" : "v3", "k4" : ["v4"] } } diff_record = get_diff(source=merge_source, target=merge_dest, action='update') s_updated = diff_record.updated assert json.loads(diff_record.delta) == dict() assert s_updated == False # nested list large_list1 = [] for i in range(1, 1000): large_list1.append(i) large_list2 = large_list1.copy() large_list2.append(1001) merge_source = { 'uuid': '10342eae-c840-5c95-ad3b-4dd680a81a0f', "k1" : "v1", "k2" : { "k3" : "v3", "k4" : large_list1 } } merge_dest = { 'uuid': '10342eae-c840-5c95-ad3b-4dd680a81a0f', "k1" : "v1", "k2" : { "k3" : "v3", "k4" : large_list2 } } diff_record = get_diff(source=merge_source, target=merge_dest, action='update') s_updated = diff_record.updated assert json.loads(diff_record.delta) == {'k2': {'k4': ['1001']}} assert s_updated == True #flip merge_source = { 'uuid': '10342eae-c840-5c95-ad3b-4dd680a81a0f', "k1" : "v1", "k2" : { "k3" : "v3", "k4" : large_list2 } } merge_dest = { 'uuid': '10342eae-c840-5c95-ad3b-4dd680a81a0f', "k1" : "v1", "k2" : { "k3" : "v3", "k4" : large_list1 } } diff_record = get_diff(source=merge_source, target=merge_dest, action='update') s_updated = diff_record.updated assert json.loads(diff_record.delta) == {'k2': {'k4': ['1001']}} assert s_updated == True # nested list of objects merge_source = { 'uuid': '10342eae-c840-5c95-ad3b-4dd680a81a0f', "k1" : "v1", "k2" : [ { "k3" : "v3" }, { "k4" : large_list2 } ] } merge_dest = { 'uuid': '10342eae-c840-5c95-ad3b-4dd680a81a0f', "k1" : "v1", "k2" : [ { "k3" : "v3",}, { "k4" : large_list1 } ] } diff_record = get_diff(source=merge_source, target=merge_dest, action='update') s_updated = diff_record.updated assert json.loads(diff_record.delta) == {'k2_1': {'k4': ['1001']}} assert s_updated == True # flip merge_source = { 'uuid': '10342eae-c840-5c95-ad3b-4dd680a81a0f', "k1" : "v1", "k2" : [ { "k3" : "v3" }, { "k4" : large_list1 } ] } merge_dest = { 'uuid': '10342eae-c840-5c95-ad3b-4dd680a81a0f', "k1" : "v1", "k2" : [ { "k3" : "v3",}, { "k4" : large_list2 } ] } diff_record = get_diff(source=merge_source, target=merge_dest, action='update') s_updated = diff_record.updated assert json.loads(diff_record.delta) == {'k2_1': {'k4': ['1001']}} assert s_updated == True # deep nest merge_source = { 'uuid': '10342eae-c840-5c95-ad3b-4dd680a81a0f', "k1" : "v1", "k2" : { "k3" : "v3", "k4" : { "k5" : "v5", "k6" : large_list1 } } } merge_dest = { 'uuid': '10342eae-c840-5c95-ad3b-4dd680a81a0f', "k1" : "v1", "k2" : { "k3" : "v3", "k4" : { "k5" : "v5", "k6" : large_list2 } } } diff_record = get_diff(source=merge_source, target=merge_dest, action='update') s_updated = diff_record.updated assert json.loads(diff_record.delta) == {'k2': {'k4': {'k6': ['1001']}}} assert s_updated == True # flip merge_source = { 'uuid': '10342eae-c840-5c95-ad3b-4dd680a81a0f', "k1" : "v1", "k2" : { "k3" : "v3", "k4" : { "k5" : "v5", "k6" : large_list2 } } } merge_dest = { 'uuid': '10342eae-c840-5c95-ad3b-4dd680a81a0f', "k1" : "v1", "k2" : { "k3" : "v3", "k4" : { "k5" : "v5", "k6" : large_list1 } } } diff_record = get_diff(source=merge_source, target=merge_dest, action='update') s_updated = diff_record.updated assert json.loads(diff_record.delta) == {'k2': {'k4': {'k6': ['1001']}}} assert s_updated == True

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722adedccf22bf190d9c21ebb28800cf4792c8c5

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py

Python

config.py

andyway/ethereum_analytical_db

9810dc32df7c49c53968cedc2b750db0193d993e

[ "MIT" ]

41

2019-03-29T09:05:21.000Z

2022-03-31T07:50:22.000Z

config.py

andyway/ethereum_analytical_db

9810dc32df7c49c53968cedc2b750db0193d993e

[ "MIT" ]

2

2019-04-02T15:56:59.000Z

2022-03-05T19:04:59.000Z

config.py

andyway/ethereum_analytical_db

9810dc32df7c49c53968cedc2b750db0193d993e

[ "MIT" ]

6

2020-10-25T04:12:12.000Z

2021-09-08T21:20:18.000Z

from datetime import datetime # URLs of parity APIs. # You can specify block range for each URL to use different nodes for each request # Make sure you have the same config as in dockerfile.yml for each node: # --tracing=on # --jsonrpc-interface=all PARITY_HOSTS = [ (None, None, "http://localhost:8545") ] # Dictionary of table names in database. # Meaning of each table explained in Schema INDICES = { "contract": "eth_contract", "token_transaction": "eth_token_transaction", "transaction": "eth_transaction", "internal_transaction": "eth_internal_transaction", "listed_token": "eth_listed_token", "token_tx": "eth_token_transaction", "block": "eth_block", "price": "eth_token_price", "block_flag": "eth_block_flag", "contract_abi": "eth_contract_abi", "contract_block": "eth_contract_block", "transaction_input": "eth_transaction_input", "event_input": "eth_event_input", "miner_transaction": "eth_miner_transaction", "event": "eth_event", "contract_description": "eth_contract_description", "bancor_trade": "eth_bancor_trade" } # List of contract addresses to process in several operations. # All other contracts will be skipped during certain operations PROCESSED_CONTRACTS = ["0xe94327d07fc17907b4db788e5adf2ed424addff6", "0xd850942ef8811f2a866692a623011bde52a462c1", "0x9f8f72aa9304c8b593d555f12ef6589cc3a579a2", "0x744d70fdbe2ba4cf95131626614a1763df805b9e", "0xb5a5f22694352c15b00323844ad545abb2b11028", "0xfa1a856cfa3409cfa145fa4e20eb270df3eb21ab", "0xd26114cd6ee289accf82350c8d8487fedb8a0c07", "0x168296bb09e24a88805cb9c33356536b980d3fc5", "0x0d8775f648430679a709e98d2b0cb6250d2887ef", "0xa74476443119a942de498590fe1f2454d7d4ac0d", "0xd4fa1460f537bb9085d22c7bccb5dd450ef28e3a", "0x5ca9a71b1d01849c0a95490cc00559717fcf0d1d", "0xcb97e65f07da24d46bcdd078ebebd7c6e6e3d750", "0x86fa049857e0209aa7d9e616f7eb3b3b78ecfdb0", "0x05f4a42e251f2d52b8ed15e9fedaacfcef1fad27", "0xb8c77482e45f1f44de1745f52c74426c631bdd52", "0xb7cb1c96db6b22b0d3d9536e0108d062bd488f74", "0xe41d2489571d322189246dafa5ebde1f4699f498", "0xf230b790e05390fc8295f4d3f60332c93bed42e2", "0xe0b7927c4af23765cb51314a0e0521a9645f0e2a", "0xef68e7c694f40c8202821edf525de3782458639f", "0xbf2179859fc6d5bee9bf9158632dc51678a4100e", "0x1f573d6fb3f13d689ff844b4ce37794d79a7ff1c", "0x08d32b0da63e2c3bcf8019c9c5d849d7a9d791e6", "0x3893b9422cd5d70a81edeffe3d5a1c6a978310bb", "0x8f3470a7388c05ee4e7af3d01d8c722b0ff52374", "0x5af2be193a6abca9c8817001f45744777db30756", "0xd0352a019e9ab9d757776f532377aaebd36fd541", "0x419d0d8bdd9af5e606ae2232ed285aff190e711b", "0x4672bad527107471cb5067a887f4656d585a8a31", "0xb3104b4b9da82025e8b9f8fb28b3553ce2f67069", "0xa4e8c3ec456107ea67d3075bf9e3df3a75823db0", "0x618e75ac90b12c6049ba3b27f5d5f8651b0037f6", "0xb91318f35bdb262e9423bc7c7c2a3a93dd93c92c", "0xea11755ae41d889ceec39a63e6ff75a02bc1c00d", "0x0f5d2fb29fb7d3cfee444a200298f468908cc942", "0x9f5f3cfd7a32700c93f971637407ff17b91c7342", "0x818fc6c2ec5986bc6e2cbf00939d90556ab12ce5", "0x9992ec3cf6a55b00978cddf2b27bc6882d88d1ec", "0xf0ee6b27b759c9893ce4f094b49ad28fd15a23e4", "0x905e337c6c8645263d3521205aa37bf4d034e745", "0x12480e24eb5bec1a9d4369cab6a80cad3c0a377a", "0x3883f5e181fccaf8410fa61e12b59bad963fb645", "0x419c4db4b9e25d6db2ad9691ccb832c8d9fda05e", "0x595832f8fc6bf59c85c527fec3740a1b7a361269", "0x7e9e431a0b8c4d532c745b1043c7fa29a48d4fba", "0xd0a4b8946cb52f0661273bfbc6fd0e0c75fc6433", "0x01ff50f8b7f74e4f00580d9596cd3d0d6d6e326f", "0xc5bbae50781be1669306b9e001eff57a2957b09d", "0xb63b606ac810a52cca15e44bb630fd42d8d1d83d", "0x607f4c5bb672230e8672085532f7e901544a7375", "0xb64ef51c888972c908cfacf59b47c1afbc0ab8ac", "0x2d0e95bd4795d7ace0da3c0ff7b706a5970eb9d3", "0x39bb259f66e1c59d5abef88375979b4d20d98022", "0x48f775efbe4f5ece6e0df2f7b5932df56823b990", "0x38c6a68304cdefb9bec48bbfaaba5c5b47818bb2", "0xe25bcec5d3801ce3a794079bf94adf1b8ccd802d", "0x8f8221afbb33998d8584a2b05749ba73c37a938a", "0x4156d3342d5c385a87d264f90653733592000581", "0x514910771af9ca656af840dff83e8264ecf986ca", "0x41e5560054824ea6b0732e656e3ad64e20e94e45", "0xb62132e35a6c13ee1ee0f84dc5d40bad8d815206", "0x66186008c1050627f979d464eabb258860563dbe", "0xb97048628db6b661d4c2aa833e95dbe1a905b280", "0x8eb24319393716668d768dcec29356ae9cffe285", "0x983f6d60db79ea8ca4eb9968c6aff8cfa04b3c63", "0x36905fc93280f52362a1cbab151f25dc46742fb5", "0x960b236a07cf122663c4303350609a66a7b288c0", "0xf7920b0768ecb20a123fac32311d07d193381d6f", "0x8dd5fbce2f6a956c3022ba3663759011dd51e73e", "0xb98d4c97425d9908e66e53a6fdf673acca0be986", "0x809826cceab68c387726af962713b64cb5cb3cca", "0xf278c1ca969095ffddded020290cf8b5c424ace2", "0x7c5a0ce9267ed19b22f8cae653f198e3e8daf098", "0x5c3a228510d246b78a3765c20221cbf3082b44a4", "0xd4c435f5b09f855c3317c8524cb1f586e42795fa", "0x3597bfd533a99c9aa083587b074434e61eb0a258", "0x99ea4db9ee77acd40b119bd1dc4e33e1c070b80d", "0x6810e776880c02933d47db1b9fc05908e5386b96", "0xf629cbd94d3791c9250152bd8dfbdf380e2a3b9c", "0x57ad67acf9bf015e4820fbd66ea1a21bed8852ec", "0x4092678e4e78230f46a1534c0fbc8fa39780892b", "0x6ec8a24cabdc339a06a172f8223ea557055adaa5", "0x0cf0ee63788a0849fe5297f3407f701e122cc023", "0x80a7e048f37a50500351c204cb407766fa3bae7f", "0x55f93985431fc9304077687a35a1ba103dc1e081", "0xeda8b016efa8b1161208cf041cd86972eee0f31e", "0xd234bf2410a0009df9c3c63b610c09738f18ccd7", "0x014b50466590340d41307cc54dcee990c8d58aa8", "0x4dc3643dbc642b72c158e7f3d2ff232df61cb6ce", "0x46b9ad944d1059450da1163511069c718f699d31", "0xe3818504c1b32bf1557b16c238b2e01fd3149c17", "0x26e75307fc0c021472feb8f727839531f112f317", "0x3833dda0aeb6947b98ce454d89366cba8cc55528", "0x68d57c9a1c35f63e2c83ee8e49a64e9d70528d25", "0x255aa6df07540cb5d3d297f0d0d4d84cb52bc8e6", "0x408e41876cccdc0f92210600ef50372656052a38", "0x85e076361cc813a908ff672f9bad1541474402b2", "0x519475b31653e46d20cd09f9fdcf3b12bdacb4f5", "0x93e682107d1e9defb0b5ee701c71707a4b2e46bc", "0xa15c7ebe1f07caf6bff097d8a589fb8ac49ae5b3", "0xaec2e87e0a235266d9c5adc9deb4b2e29b54d009", "0x92e52a1a235d9a103d970901066ce910aacefd37"] # Size of pages received from Clickhouse BATCH_SIZE = 1000 # recommended # Max size of chunk inserted into Clickhouse MAX_CHUNK_SIZE = 20000000 # recommended, average size of block # Number of chunks processed simultaneously while extracting transactions from parity PARITY_EXTRACTION_PROCESSES = 3 # recommended # Number of chunks processed simultaneously during input parsing INPUT_PARSING_PROCESSES = 10 # recommended # Number of blocks processed simultaneously during events extraction EVENTS_RANGE_SIZE = 5 # recommended # Max memory usage for clickhouse MAX_MEMORY_USAGE = 1000000000 # recommended # API key for etherscan.io ABI extraction ETHERSCAN_API_KEY = "YourApiKeyToken" DATABASE = "clickhouse" GENESIS = "genesis.json" ETHEREUM_START_DATE = datetime(2015, 7, 30) # Node URL for tests TEST_PARITY_NODE = "http://localhost:8545/" NUMBER_OF_JOBS = BATCH_SIZE

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py

Python

ivy/array/linalg.py

saurbhc/ivy

20b327b4fab543b26ad5a18acf4deddd6e3c804b

[ "Apache-2.0" ]

161

2021-01-20T22:11:13.000Z

2022-01-09T09:46:33.000Z

ivy/array/linalg.py

saurbhc/ivy

20b327b4fab543b26ad5a18acf4deddd6e3c804b

[ "Apache-2.0" ]

4

2021-11-10T17:04:36.000Z

2021-11-26T06:40:43.000Z

ivy/array/linalg.py

saurbhc/ivy

20b327b4fab543b26ad5a18acf4deddd6e3c804b

[ "Apache-2.0" ]

8

2021-02-17T20:56:33.000Z

2022-01-09T16:45:40.000Z

# global import abc # ToDo: implement all linalg methods here as public class methods class ArrayWithLinalg(abc.ABC): pass

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7

a0d54813f9e2e5b333b7529bf7e968932b35291f

2,158

py

Python

dragon/renderhelp.py

NicEastvillage/RLBot-DropShot-Dragon-Python

b0d94fd054ab410ad02880a3d56e72b5eddd7ba6

[ "MIT" ]

1

2019-08-07T21:38:59.000Z

dragon/renderhelp.py

NicEastvillage/RLBot-DropShot-Dragon-Python

b0d94fd054ab410ad02880a3d56e72b5eddd7ba6

[ "MIT" ]

null

dragon/renderhelp.py

NicEastvillage/RLBot-DropShot-Dragon-Python

b0d94fd054ab410ad02880a3d56e72b5eddd7ba6

[ "MIT" ]

null

from RLUtilities.LinearAlgebra import vec3 import tiles def highlight_tile(renderer, tile, color): vecs = [tile.location + vec3(tiles.TILE_WIDTH / 2, tiles.TILE_SIZE / 2, 0), tile.location + vec3(0, tiles.TILE_SIZE, 0), tile.location + vec3(-tiles.TILE_WIDTH / 2, tiles.TILE_SIZE / 2, 0), tile.location + vec3(-tiles.TILE_WIDTH / 2, -tiles.TILE_SIZE / 2, 0), tile.location + vec3(0, -tiles.TILE_SIZE, 0), tile.location + vec3(tiles.TILE_WIDTH / 2, -tiles.TILE_SIZE / 2, 0), tile.location + vec3(tiles.TILE_WIDTH / 2, tiles.TILE_SIZE / 2, 0)] renderer.draw_polyline_3d(vecs, color) def highlight_tile_more(renderer, tile, color): vecs = [tile.location + vec3(tiles.TILE_WIDTH / 2, tiles.TILE_SIZE / 2, 0), tile.location + vec3(0, tiles.TILE_SIZE, 0), tile.location + vec3(-tiles.TILE_WIDTH / 2, tiles.TILE_SIZE / 2, 0), tile.location + vec3(-tiles.TILE_WIDTH / 2, -tiles.TILE_SIZE / 2, 0), tile.location + vec3(0, -tiles.TILE_SIZE, 0), tile.location + vec3(tiles.TILE_WIDTH / 2, -tiles.TILE_SIZE / 2, 0)] for i in range(6): for j in range(i + 1, 6): renderer.draw_line_3d(vecs[i], vecs[j], color) def highlight_point_on_tile(renderer, info, point, color): flat = vec3(point[0], point[1], 0) tile = tiles.point_to_tile(info, point) renderer.draw_line_3d(point, flat, color) if tile != None: vecs = [tile.location + vec3(tiles.TILE_WIDTH / 2, tiles.TILE_SIZE / 2, 0), tile.location + vec3(0, tiles.TILE_SIZE, 0), tile.location + vec3(-tiles.TILE_WIDTH / 2, tiles.TILE_SIZE / 2, 0), tile.location + vec3(-tiles.TILE_WIDTH / 2, -tiles.TILE_SIZE / 2, 0), tile.location + vec3(0, -tiles.TILE_SIZE, 0), tile.location + vec3(tiles.TILE_WIDTH / 2, -tiles.TILE_SIZE / 2, 0), tile.location + vec3(tiles.TILE_WIDTH / 2, tiles.TILE_SIZE / 2, 0)] renderer.draw_polyline_3d(vecs, color) for i in range(6): renderer.draw_line_3d(flat, vecs[i], color)

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a0ed8b10a60a643944262a5556fb03ff915ca586

166

py

Python

pyrobolearn/tools/bridges/audio/__init__.py

Pandinosaurus/pyrobolearn

9cd7c060723fda7d2779fa255ac998c2c82b8436

[ "Apache-2.0" ]

2

2021-01-21T21:08:30.000Z

2022-03-29T16:45:49.000Z

pyrobolearn/tools/bridges/audio/__init__.py

Pandinosaurus/pyrobolearn

9cd7c060723fda7d2779fa255ac998c2c82b8436

[ "Apache-2.0" ]

null

pyrobolearn/tools/bridges/audio/__init__.py

Pandinosaurus/pyrobolearn

9cd7c060723fda7d2779fa255ac998c2c82b8436

[ "Apache-2.0" ]

1

2020-09-29T21:25:39.000Z

# -*- coding: utf-8 -*- # Bridge for audio interfaces # # Bridge between audio and robot from . import robots # Bridge between audio and world from . import world

16.6

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