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6cf7c8938f7ceca38c2736fba43ed8ef4a46a14b2f0c1c1a3e2847900d0ba1cc
|
@property
@pulumi.getter
def key(self) -> pulumi.Input[str]:
'\n The label key that the selector applies to.\n '
return pulumi.get(self, 'key')
|
The label key that the selector applies to.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
key
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter
def key(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'key')
|
@property
@pulumi.getter
def key(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'key')<|docstring|>The label key that the selector applies to.<|endoftext|>
|
026834ef706ec81b0dac6449994d81a644e4e6273652b199546c01310ae542ba
|
@property
@pulumi.getter
def operator(self) -> pulumi.Input[str]:
"\n Represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists, DoesNotExist. Gt, and Lt.\n "
return pulumi.get(self, 'operator')
|
Represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists, DoesNotExist. Gt, and Lt.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
operator
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter
def operator(self) -> pulumi.Input[str]:
"\n \n "
return pulumi.get(self, 'operator')
|
@property
@pulumi.getter
def operator(self) -> pulumi.Input[str]:
"\n \n "
return pulumi.get(self, 'operator')<|docstring|>Represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists, DoesNotExist. Gt, and Lt.<|endoftext|>
|
1156c9e0af0cbb14c25f97914f22f3802e172355689d41403da88d3ce78227b5
|
@property
@pulumi.getter
def values(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
'\n An array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. If the operator is Gt or Lt, the values array must have a single element, which will be interpreted as an integer. This array is replaced during a strategic merge patch.\n '
return pulumi.get(self, 'values')
|
An array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. If the operator is Gt or Lt, the values array must have a single element, which will be interpreted as an integer. This array is replaced during a strategic merge patch.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
values
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter
def values(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
'\n \n '
return pulumi.get(self, 'values')
|
@property
@pulumi.getter
def values(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
'\n \n '
return pulumi.get(self, 'values')<|docstring|>An array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. If the operator is Gt or Lt, the values array must have a single element, which will be interpreted as an integer. This array is replaced during a strategic merge patch.<|endoftext|>
|
57c9e894aa291b9c40773ebd68d1e6baed160d9adcd1f724cc2823e7fb689af0
|
def __init__(__self__, *, preferred_during_scheduling_ignored_during_execution: Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionArgs']]]]=None, required_during_scheduling_ignored_during_execution: Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionArgs']]]]=None):
'\n Describes pod affinity scheduling rules (e.g. co-locate this pod in the same node, zone, etc. as some other pod(s)).\n :param pulumi.Input[Sequence[pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionArgs\']]] preferred_during_scheduling_ignored_during_execution: The scheduler will prefer to schedule pods to nodes that satisfy the affinity expressions specified by this field, but it may choose a node that violates one or more of the expressions. The node that is most preferred is the one with the greatest sum of weights, i.e. for each node that meets all of the scheduling requirements (resource request, requiredDuringScheduling affinity expressions, etc.), compute a sum by iterating through the elements of this field and adding "weight" to the sum if the node has pods which matches the corresponding podAffinityTerm; the node(s) with the highest sum are the most preferred.\n :param pulumi.Input[Sequence[pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionArgs\']]] required_during_scheduling_ignored_during_execution: If the affinity requirements specified by this field are not met at scheduling time, the pod will not be scheduled onto the node. If the affinity requirements specified by this field cease to be met at some point during pod execution (e.g. due to a pod label update), the system may or may not try to eventually evict the pod from its node. When there are multiple elements, the lists of nodes corresponding to each podAffinityTerm are intersected, i.e. all terms must be satisfied.\n '
if (preferred_during_scheduling_ignored_during_execution is not None):
pulumi.set(__self__, 'preferred_during_scheduling_ignored_during_execution', preferred_during_scheduling_ignored_during_execution)
if (required_during_scheduling_ignored_during_execution is not None):
pulumi.set(__self__, 'required_during_scheduling_ignored_during_execution', required_during_scheduling_ignored_during_execution)
|
Describes pod affinity scheduling rules (e.g. co-locate this pod in the same node, zone, etc. as some other pod(s)).
:param pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionArgs']]] preferred_during_scheduling_ignored_during_execution: The scheduler will prefer to schedule pods to nodes that satisfy the affinity expressions specified by this field, but it may choose a node that violates one or more of the expressions. The node that is most preferred is the one with the greatest sum of weights, i.e. for each node that meets all of the scheduling requirements (resource request, requiredDuringScheduling affinity expressions, etc.), compute a sum by iterating through the elements of this field and adding "weight" to the sum if the node has pods which matches the corresponding podAffinityTerm; the node(s) with the highest sum are the most preferred.
:param pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionArgs']]] required_during_scheduling_ignored_during_execution: If the affinity requirements specified by this field are not met at scheduling time, the pod will not be scheduled onto the node. If the affinity requirements specified by this field cease to be met at some point during pod execution (e.g. due to a pod label update), the system may or may not try to eventually evict the pod from its node. When there are multiple elements, the lists of nodes corresponding to each podAffinityTerm are intersected, i.e. all terms must be satisfied.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
__init__
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
def __init__(__self__, *, preferred_during_scheduling_ignored_during_execution: Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionArgs']]]]=None, required_during_scheduling_ignored_during_execution: Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionArgs']]]]=None):
'\n Describes pod affinity scheduling rules (e.g. co-locate this pod in the same node, zone, etc. as some other pod(s)).\n :param pulumi.Input[Sequence[pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionArgs\']]] preferred_during_scheduling_ignored_during_execution: The scheduler will prefer to schedule pods to nodes that satisfy the affinity expressions specified by this field, but it may choose a node that violates one or more of the expressions. The node that is most preferred is the one with the greatest sum of weights, i.e. for each node that meets all of the scheduling requirements (resource request, requiredDuringScheduling affinity expressions, etc.), compute a sum by iterating through the elements of this field and adding "weight" to the sum if the node has pods which matches the corresponding podAffinityTerm; the node(s) with the highest sum are the most preferred.\n :param pulumi.Input[Sequence[pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionArgs\']]] required_during_scheduling_ignored_during_execution: If the affinity requirements specified by this field are not met at scheduling time, the pod will not be scheduled onto the node. If the affinity requirements specified by this field cease to be met at some point during pod execution (e.g. due to a pod label update), the system may or may not try to eventually evict the pod from its node. When there are multiple elements, the lists of nodes corresponding to each podAffinityTerm are intersected, i.e. all terms must be satisfied.\n '
if (preferred_during_scheduling_ignored_during_execution is not None):
pulumi.set(__self__, 'preferred_during_scheduling_ignored_during_execution', preferred_during_scheduling_ignored_during_execution)
if (required_during_scheduling_ignored_during_execution is not None):
pulumi.set(__self__, 'required_during_scheduling_ignored_during_execution', required_during_scheduling_ignored_during_execution)
|
def __init__(__self__, *, preferred_during_scheduling_ignored_during_execution: Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionArgs']]]]=None, required_during_scheduling_ignored_during_execution: Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionArgs']]]]=None):
'\n Describes pod affinity scheduling rules (e.g. co-locate this pod in the same node, zone, etc. as some other pod(s)).\n :param pulumi.Input[Sequence[pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionArgs\']]] preferred_during_scheduling_ignored_during_execution: The scheduler will prefer to schedule pods to nodes that satisfy the affinity expressions specified by this field, but it may choose a node that violates one or more of the expressions. The node that is most preferred is the one with the greatest sum of weights, i.e. for each node that meets all of the scheduling requirements (resource request, requiredDuringScheduling affinity expressions, etc.), compute a sum by iterating through the elements of this field and adding "weight" to the sum if the node has pods which matches the corresponding podAffinityTerm; the node(s) with the highest sum are the most preferred.\n :param pulumi.Input[Sequence[pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionArgs\']]] required_during_scheduling_ignored_during_execution: If the affinity requirements specified by this field are not met at scheduling time, the pod will not be scheduled onto the node. If the affinity requirements specified by this field cease to be met at some point during pod execution (e.g. due to a pod label update), the system may or may not try to eventually evict the pod from its node. When there are multiple elements, the lists of nodes corresponding to each podAffinityTerm are intersected, i.e. all terms must be satisfied.\n '
if (preferred_during_scheduling_ignored_during_execution is not None):
pulumi.set(__self__, 'preferred_during_scheduling_ignored_during_execution', preferred_during_scheduling_ignored_during_execution)
if (required_during_scheduling_ignored_during_execution is not None):
pulumi.set(__self__, 'required_during_scheduling_ignored_during_execution', required_during_scheduling_ignored_during_execution)<|docstring|>Describes pod affinity scheduling rules (e.g. co-locate this pod in the same node, zone, etc. as some other pod(s)).
:param pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionArgs']]] preferred_during_scheduling_ignored_during_execution: The scheduler will prefer to schedule pods to nodes that satisfy the affinity expressions specified by this field, but it may choose a node that violates one or more of the expressions. The node that is most preferred is the one with the greatest sum of weights, i.e. for each node that meets all of the scheduling requirements (resource request, requiredDuringScheduling affinity expressions, etc.), compute a sum by iterating through the elements of this field and adding "weight" to the sum if the node has pods which matches the corresponding podAffinityTerm; the node(s) with the highest sum are the most preferred.
:param pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionArgs']]] required_during_scheduling_ignored_during_execution: If the affinity requirements specified by this field are not met at scheduling time, the pod will not be scheduled onto the node. If the affinity requirements specified by this field cease to be met at some point during pod execution (e.g. due to a pod label update), the system may or may not try to eventually evict the pod from its node. When there are multiple elements, the lists of nodes corresponding to each podAffinityTerm are intersected, i.e. all terms must be satisfied.<|endoftext|>
|
837111f6474521c650fe424bbf103b07e8d58bbc33e85a92a366063efa7a2a38
|
@property
@pulumi.getter(name='preferredDuringSchedulingIgnoredDuringExecution')
def preferred_during_scheduling_ignored_during_execution(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionArgs']]]]:
'\n The scheduler will prefer to schedule pods to nodes that satisfy the affinity expressions specified by this field, but it may choose a node that violates one or more of the expressions. The node that is most preferred is the one with the greatest sum of weights, i.e. for each node that meets all of the scheduling requirements (resource request, requiredDuringScheduling affinity expressions, etc.), compute a sum by iterating through the elements of this field and adding "weight" to the sum if the node has pods which matches the corresponding podAffinityTerm; the node(s) with the highest sum are the most preferred.\n '
return pulumi.get(self, 'preferred_during_scheduling_ignored_during_execution')
|
The scheduler will prefer to schedule pods to nodes that satisfy the affinity expressions specified by this field, but it may choose a node that violates one or more of the expressions. The node that is most preferred is the one with the greatest sum of weights, i.e. for each node that meets all of the scheduling requirements (resource request, requiredDuringScheduling affinity expressions, etc.), compute a sum by iterating through the elements of this field and adding "weight" to the sum if the node has pods which matches the corresponding podAffinityTerm; the node(s) with the highest sum are the most preferred.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
preferred_during_scheduling_ignored_during_execution
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter(name='preferredDuringSchedulingIgnoredDuringExecution')
def preferred_during_scheduling_ignored_during_execution(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionArgs']]]]:
'\n \n '
return pulumi.get(self, 'preferred_during_scheduling_ignored_during_execution')
|
@property
@pulumi.getter(name='preferredDuringSchedulingIgnoredDuringExecution')
def preferred_during_scheduling_ignored_during_execution(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionArgs']]]]:
'\n \n '
return pulumi.get(self, 'preferred_during_scheduling_ignored_during_execution')<|docstring|>The scheduler will prefer to schedule pods to nodes that satisfy the affinity expressions specified by this field, but it may choose a node that violates one or more of the expressions. The node that is most preferred is the one with the greatest sum of weights, i.e. for each node that meets all of the scheduling requirements (resource request, requiredDuringScheduling affinity expressions, etc.), compute a sum by iterating through the elements of this field and adding "weight" to the sum if the node has pods which matches the corresponding podAffinityTerm; the node(s) with the highest sum are the most preferred.<|endoftext|>
|
bb1da76b1a1f6312c26174555c95998b360d9a130f64b4758b094b6a8afff3cb
|
@property
@pulumi.getter(name='requiredDuringSchedulingIgnoredDuringExecution')
def required_during_scheduling_ignored_during_execution(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionArgs']]]]:
'\n If the affinity requirements specified by this field are not met at scheduling time, the pod will not be scheduled onto the node. If the affinity requirements specified by this field cease to be met at some point during pod execution (e.g. due to a pod label update), the system may or may not try to eventually evict the pod from its node. When there are multiple elements, the lists of nodes corresponding to each podAffinityTerm are intersected, i.e. all terms must be satisfied.\n '
return pulumi.get(self, 'required_during_scheduling_ignored_during_execution')
|
If the affinity requirements specified by this field are not met at scheduling time, the pod will not be scheduled onto the node. If the affinity requirements specified by this field cease to be met at some point during pod execution (e.g. due to a pod label update), the system may or may not try to eventually evict the pod from its node. When there are multiple elements, the lists of nodes corresponding to each podAffinityTerm are intersected, i.e. all terms must be satisfied.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
required_during_scheduling_ignored_during_execution
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter(name='requiredDuringSchedulingIgnoredDuringExecution')
def required_during_scheduling_ignored_during_execution(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionArgs']]]]:
'\n \n '
return pulumi.get(self, 'required_during_scheduling_ignored_during_execution')
|
@property
@pulumi.getter(name='requiredDuringSchedulingIgnoredDuringExecution')
def required_during_scheduling_ignored_during_execution(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionArgs']]]]:
'\n \n '
return pulumi.get(self, 'required_during_scheduling_ignored_during_execution')<|docstring|>If the affinity requirements specified by this field are not met at scheduling time, the pod will not be scheduled onto the node. If the affinity requirements specified by this field cease to be met at some point during pod execution (e.g. due to a pod label update), the system may or may not try to eventually evict the pod from its node. When there are multiple elements, the lists of nodes corresponding to each podAffinityTerm are intersected, i.e. all terms must be satisfied.<|endoftext|>
|
8cd6dfb1e2062325c56a0d0f9083f53db00af1b6e957176ce64e7d54512232e3
|
def __init__(__self__, *, pod_affinity_term: pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermArgs'], weight: pulumi.Input[int]):
"\n The weights of all of the matched WeightedPodAffinityTerm fields are added per-node to find the most preferred node(s)\n :param pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermArgs'] pod_affinity_term: Required. A pod affinity term, associated with the corresponding weight.\n :param pulumi.Input[int] weight: weight associated with matching the corresponding podAffinityTerm, in the range 1-100.\n "
pulumi.set(__self__, 'pod_affinity_term', pod_affinity_term)
pulumi.set(__self__, 'weight', weight)
|
The weights of all of the matched WeightedPodAffinityTerm fields are added per-node to find the most preferred node(s)
:param pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermArgs'] pod_affinity_term: Required. A pod affinity term, associated with the corresponding weight.
:param pulumi.Input[int] weight: weight associated with matching the corresponding podAffinityTerm, in the range 1-100.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
__init__
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
def __init__(__self__, *, pod_affinity_term: pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermArgs'], weight: pulumi.Input[int]):
"\n The weights of all of the matched WeightedPodAffinityTerm fields are added per-node to find the most preferred node(s)\n :param pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermArgs'] pod_affinity_term: Required. A pod affinity term, associated with the corresponding weight.\n :param pulumi.Input[int] weight: weight associated with matching the corresponding podAffinityTerm, in the range 1-100.\n "
pulumi.set(__self__, 'pod_affinity_term', pod_affinity_term)
pulumi.set(__self__, 'weight', weight)
|
def __init__(__self__, *, pod_affinity_term: pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermArgs'], weight: pulumi.Input[int]):
"\n The weights of all of the matched WeightedPodAffinityTerm fields are added per-node to find the most preferred node(s)\n :param pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermArgs'] pod_affinity_term: Required. A pod affinity term, associated with the corresponding weight.\n :param pulumi.Input[int] weight: weight associated with matching the corresponding podAffinityTerm, in the range 1-100.\n "
pulumi.set(__self__, 'pod_affinity_term', pod_affinity_term)
pulumi.set(__self__, 'weight', weight)<|docstring|>The weights of all of the matched WeightedPodAffinityTerm fields are added per-node to find the most preferred node(s)
:param pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermArgs'] pod_affinity_term: Required. A pod affinity term, associated with the corresponding weight.
:param pulumi.Input[int] weight: weight associated with matching the corresponding podAffinityTerm, in the range 1-100.<|endoftext|>
|
7c0ea4baa6aef8ddf9ca57a39b02b8d8ed0755a1d1100abc1182070798b18980
|
@property
@pulumi.getter(name='podAffinityTerm')
def pod_affinity_term(self) -> pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermArgs']:
'\n Required. A pod affinity term, associated with the corresponding weight.\n '
return pulumi.get(self, 'pod_affinity_term')
|
Required. A pod affinity term, associated with the corresponding weight.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
pod_affinity_term
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter(name='podAffinityTerm')
def pod_affinity_term(self) -> pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermArgs']:
'\n \n '
return pulumi.get(self, 'pod_affinity_term')
|
@property
@pulumi.getter(name='podAffinityTerm')
def pod_affinity_term(self) -> pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermArgs']:
'\n \n '
return pulumi.get(self, 'pod_affinity_term')<|docstring|>Required. A pod affinity term, associated with the corresponding weight.<|endoftext|>
|
cbda27b0cdf343ea47c23ff8abbfa8a96b716aaf51975c7c3ed2982e4a3adb2f
|
@property
@pulumi.getter
def weight(self) -> pulumi.Input[int]:
'\n weight associated with matching the corresponding podAffinityTerm, in the range 1-100.\n '
return pulumi.get(self, 'weight')
|
weight associated with matching the corresponding podAffinityTerm, in the range 1-100.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
weight
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter
def weight(self) -> pulumi.Input[int]:
'\n \n '
return pulumi.get(self, 'weight')
|
@property
@pulumi.getter
def weight(self) -> pulumi.Input[int]:
'\n \n '
return pulumi.get(self, 'weight')<|docstring|>weight associated with matching the corresponding podAffinityTerm, in the range 1-100.<|endoftext|>
|
84fa5243527043a1fd72de1c908ae42c5f1419f5b209d54d35f47f1b03a4bb51
|
def __init__(__self__, *, topology_key: pulumi.Input[str], label_selector: Optional[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorArgs']]=None, namespaces: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]=None):
'\n Required. A pod affinity term, associated with the corresponding weight.\n :param pulumi.Input[str] topology_key: This pod should be co-located (affinity) or not co-located (anti-affinity) with the pods matching the labelSelector in the specified namespaces, where co-located is defined as running on a node whose value of the label with key topologyKey matches that of any node on which any of the selected pods is running. Empty topologyKey is not allowed.\n :param pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorArgs\'] label_selector: A label query over a set of resources, in this case pods.\n :param pulumi.Input[Sequence[pulumi.Input[str]]] namespaces: namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod\'s namespace"\n '
pulumi.set(__self__, 'topology_key', topology_key)
if (label_selector is not None):
pulumi.set(__self__, 'label_selector', label_selector)
if (namespaces is not None):
pulumi.set(__self__, 'namespaces', namespaces)
|
Required. A pod affinity term, associated with the corresponding weight.
:param pulumi.Input[str] topology_key: This pod should be co-located (affinity) or not co-located (anti-affinity) with the pods matching the labelSelector in the specified namespaces, where co-located is defined as running on a node whose value of the label with key topologyKey matches that of any node on which any of the selected pods is running. Empty topologyKey is not allowed.
:param pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorArgs'] label_selector: A label query over a set of resources, in this case pods.
:param pulumi.Input[Sequence[pulumi.Input[str]]] namespaces: namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod's namespace"
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
__init__
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
def __init__(__self__, *, topology_key: pulumi.Input[str], label_selector: Optional[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorArgs']]=None, namespaces: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]=None):
'\n Required. A pod affinity term, associated with the corresponding weight.\n :param pulumi.Input[str] topology_key: This pod should be co-located (affinity) or not co-located (anti-affinity) with the pods matching the labelSelector in the specified namespaces, where co-located is defined as running on a node whose value of the label with key topologyKey matches that of any node on which any of the selected pods is running. Empty topologyKey is not allowed.\n :param pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorArgs\'] label_selector: A label query over a set of resources, in this case pods.\n :param pulumi.Input[Sequence[pulumi.Input[str]]] namespaces: namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod\'s namespace"\n '
pulumi.set(__self__, 'topology_key', topology_key)
if (label_selector is not None):
pulumi.set(__self__, 'label_selector', label_selector)
if (namespaces is not None):
pulumi.set(__self__, 'namespaces', namespaces)
|
def __init__(__self__, *, topology_key: pulumi.Input[str], label_selector: Optional[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorArgs']]=None, namespaces: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]=None):
'\n Required. A pod affinity term, associated with the corresponding weight.\n :param pulumi.Input[str] topology_key: This pod should be co-located (affinity) or not co-located (anti-affinity) with the pods matching the labelSelector in the specified namespaces, where co-located is defined as running on a node whose value of the label with key topologyKey matches that of any node on which any of the selected pods is running. Empty topologyKey is not allowed.\n :param pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorArgs\'] label_selector: A label query over a set of resources, in this case pods.\n :param pulumi.Input[Sequence[pulumi.Input[str]]] namespaces: namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod\'s namespace"\n '
pulumi.set(__self__, 'topology_key', topology_key)
if (label_selector is not None):
pulumi.set(__self__, 'label_selector', label_selector)
if (namespaces is not None):
pulumi.set(__self__, 'namespaces', namespaces)<|docstring|>Required. A pod affinity term, associated with the corresponding weight.
:param pulumi.Input[str] topology_key: This pod should be co-located (affinity) or not co-located (anti-affinity) with the pods matching the labelSelector in the specified namespaces, where co-located is defined as running on a node whose value of the label with key topologyKey matches that of any node on which any of the selected pods is running. Empty topologyKey is not allowed.
:param pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorArgs'] label_selector: A label query over a set of resources, in this case pods.
:param pulumi.Input[Sequence[pulumi.Input[str]]] namespaces: namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod's namespace"<|endoftext|>
|
1a7fd32bfbac3e1d1c7b3da8ebc96670c998ac5294448293ae6cf957310d8ab3
|
@property
@pulumi.getter(name='topologyKey')
def topology_key(self) -> pulumi.Input[str]:
'\n This pod should be co-located (affinity) or not co-located (anti-affinity) with the pods matching the labelSelector in the specified namespaces, where co-located is defined as running on a node whose value of the label with key topologyKey matches that of any node on which any of the selected pods is running. Empty topologyKey is not allowed.\n '
return pulumi.get(self, 'topology_key')
|
This pod should be co-located (affinity) or not co-located (anti-affinity) with the pods matching the labelSelector in the specified namespaces, where co-located is defined as running on a node whose value of the label with key topologyKey matches that of any node on which any of the selected pods is running. Empty topologyKey is not allowed.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
topology_key
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter(name='topologyKey')
def topology_key(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'topology_key')
|
@property
@pulumi.getter(name='topologyKey')
def topology_key(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'topology_key')<|docstring|>This pod should be co-located (affinity) or not co-located (anti-affinity) with the pods matching the labelSelector in the specified namespaces, where co-located is defined as running on a node whose value of the label with key topologyKey matches that of any node on which any of the selected pods is running. Empty topologyKey is not allowed.<|endoftext|>
|
ed9d0baa91509a37d44c08760ddbb4ebdde598a0fac17398e60e9fa10da23b90
|
@property
@pulumi.getter(name='labelSelector')
def label_selector(self) -> Optional[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorArgs']]:
'\n A label query over a set of resources, in this case pods.\n '
return pulumi.get(self, 'label_selector')
|
A label query over a set of resources, in this case pods.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
label_selector
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter(name='labelSelector')
def label_selector(self) -> Optional[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorArgs']]:
'\n \n '
return pulumi.get(self, 'label_selector')
|
@property
@pulumi.getter(name='labelSelector')
def label_selector(self) -> Optional[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorArgs']]:
'\n \n '
return pulumi.get(self, 'label_selector')<|docstring|>A label query over a set of resources, in this case pods.<|endoftext|>
|
cafaaebd0b2bde715d14eccb6c5349f21790206a44c76155207e11f20235f51a
|
@property
@pulumi.getter
def namespaces(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
'\n namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod\'s namespace"\n '
return pulumi.get(self, 'namespaces')
|
namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod's namespace"
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
namespaces
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter
def namespaces(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
'\n namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod\'s namespace"\n '
return pulumi.get(self, 'namespaces')
|
@property
@pulumi.getter
def namespaces(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
'\n namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod\'s namespace"\n '
return pulumi.get(self, 'namespaces')<|docstring|>namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod's namespace"<|endoftext|>
|
bd67f66d19745ee0efd8236807b7aa8721b3fe938af84960d711ca2cf5a3b7e6
|
def __init__(__self__, *, match_expressions: Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorMatchExpressionsArgs']]]]=None, match_labels: Optional[pulumi.Input[Mapping[(str, pulumi.Input[str])]]]=None):
'\n A label query over a set of resources, in this case pods.\n :param pulumi.Input[Sequence[pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorMatchExpressionsArgs\']]] match_expressions: matchExpressions is a list of label selector requirements. The requirements are ANDed.\n :param pulumi.Input[Mapping[str, pulumi.Input[str]]] match_labels: matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed.\n '
if (match_expressions is not None):
pulumi.set(__self__, 'match_expressions', match_expressions)
if (match_labels is not None):
pulumi.set(__self__, 'match_labels', match_labels)
|
A label query over a set of resources, in this case pods.
:param pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorMatchExpressionsArgs']]] match_expressions: matchExpressions is a list of label selector requirements. The requirements are ANDed.
:param pulumi.Input[Mapping[str, pulumi.Input[str]]] match_labels: matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
__init__
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
def __init__(__self__, *, match_expressions: Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorMatchExpressionsArgs']]]]=None, match_labels: Optional[pulumi.Input[Mapping[(str, pulumi.Input[str])]]]=None):
'\n A label query over a set of resources, in this case pods.\n :param pulumi.Input[Sequence[pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorMatchExpressionsArgs\']]] match_expressions: matchExpressions is a list of label selector requirements. The requirements are ANDed.\n :param pulumi.Input[Mapping[str, pulumi.Input[str]]] match_labels: matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed.\n '
if (match_expressions is not None):
pulumi.set(__self__, 'match_expressions', match_expressions)
if (match_labels is not None):
pulumi.set(__self__, 'match_labels', match_labels)
|
def __init__(__self__, *, match_expressions: Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorMatchExpressionsArgs']]]]=None, match_labels: Optional[pulumi.Input[Mapping[(str, pulumi.Input[str])]]]=None):
'\n A label query over a set of resources, in this case pods.\n :param pulumi.Input[Sequence[pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorMatchExpressionsArgs\']]] match_expressions: matchExpressions is a list of label selector requirements. The requirements are ANDed.\n :param pulumi.Input[Mapping[str, pulumi.Input[str]]] match_labels: matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed.\n '
if (match_expressions is not None):
pulumi.set(__self__, 'match_expressions', match_expressions)
if (match_labels is not None):
pulumi.set(__self__, 'match_labels', match_labels)<|docstring|>A label query over a set of resources, in this case pods.
:param pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorMatchExpressionsArgs']]] match_expressions: matchExpressions is a list of label selector requirements. The requirements are ANDed.
:param pulumi.Input[Mapping[str, pulumi.Input[str]]] match_labels: matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed.<|endoftext|>
|
0c2aeb6bbe462ee058516bd6abbdcf2907548a7f01973ff2b0c4aa0659feb180
|
@property
@pulumi.getter(name='matchExpressions')
def match_expressions(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorMatchExpressionsArgs']]]]:
'\n matchExpressions is a list of label selector requirements. The requirements are ANDed.\n '
return pulumi.get(self, 'match_expressions')
|
matchExpressions is a list of label selector requirements. The requirements are ANDed.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
match_expressions
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter(name='matchExpressions')
def match_expressions(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorMatchExpressionsArgs']]]]:
'\n \n '
return pulumi.get(self, 'match_expressions')
|
@property
@pulumi.getter(name='matchExpressions')
def match_expressions(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorMatchExpressionsArgs']]]]:
'\n \n '
return pulumi.get(self, 'match_expressions')<|docstring|>matchExpressions is a list of label selector requirements. The requirements are ANDed.<|endoftext|>
|
c8d28c22c7664eea6a56b076ef07546eb4ceb965de2e9c944999569f79409a76
|
@property
@pulumi.getter(name='matchLabels')
def match_labels(self) -> Optional[pulumi.Input[Mapping[(str, pulumi.Input[str])]]]:
'\n matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed.\n '
return pulumi.get(self, 'match_labels')
|
matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
match_labels
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter(name='matchLabels')
def match_labels(self) -> Optional[pulumi.Input[Mapping[(str, pulumi.Input[str])]]]:
'\n \n '
return pulumi.get(self, 'match_labels')
|
@property
@pulumi.getter(name='matchLabels')
def match_labels(self) -> Optional[pulumi.Input[Mapping[(str, pulumi.Input[str])]]]:
'\n \n '
return pulumi.get(self, 'match_labels')<|docstring|>matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed.<|endoftext|>
|
c920819fc0b4fc3fe978eacb8fbb8d5f1500cc63d1fed6bf3274b88c2f2ce017
|
def __init__(__self__, *, key: pulumi.Input[str], operator: pulumi.Input[str], values: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]=None):
"\n A label selector requirement is a selector that contains values, a key, and an operator that relates the key and values.\n :param pulumi.Input[str] key: key is the label key that the selector applies to.\n :param pulumi.Input[str] operator: operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist.\n :param pulumi.Input[Sequence[pulumi.Input[str]]] values: values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch.\n "
pulumi.set(__self__, 'key', key)
pulumi.set(__self__, 'operator', operator)
if (values is not None):
pulumi.set(__self__, 'values', values)
|
A label selector requirement is a selector that contains values, a key, and an operator that relates the key and values.
:param pulumi.Input[str] key: key is the label key that the selector applies to.
:param pulumi.Input[str] operator: operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist.
:param pulumi.Input[Sequence[pulumi.Input[str]]] values: values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
__init__
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
def __init__(__self__, *, key: pulumi.Input[str], operator: pulumi.Input[str], values: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]=None):
"\n A label selector requirement is a selector that contains values, a key, and an operator that relates the key and values.\n :param pulumi.Input[str] key: key is the label key that the selector applies to.\n :param pulumi.Input[str] operator: operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist.\n :param pulumi.Input[Sequence[pulumi.Input[str]]] values: values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch.\n "
pulumi.set(__self__, 'key', key)
pulumi.set(__self__, 'operator', operator)
if (values is not None):
pulumi.set(__self__, 'values', values)
|
def __init__(__self__, *, key: pulumi.Input[str], operator: pulumi.Input[str], values: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]=None):
"\n A label selector requirement is a selector that contains values, a key, and an operator that relates the key and values.\n :param pulumi.Input[str] key: key is the label key that the selector applies to.\n :param pulumi.Input[str] operator: operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist.\n :param pulumi.Input[Sequence[pulumi.Input[str]]] values: values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch.\n "
pulumi.set(__self__, 'key', key)
pulumi.set(__self__, 'operator', operator)
if (values is not None):
pulumi.set(__self__, 'values', values)<|docstring|>A label selector requirement is a selector that contains values, a key, and an operator that relates the key and values.
:param pulumi.Input[str] key: key is the label key that the selector applies to.
:param pulumi.Input[str] operator: operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist.
:param pulumi.Input[Sequence[pulumi.Input[str]]] values: values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch.<|endoftext|>
|
873b01de6c7b4b390af7286e21dc936c9a738bde5f172c97010521d8ead34b94
|
@property
@pulumi.getter
def key(self) -> pulumi.Input[str]:
'\n key is the label key that the selector applies to.\n '
return pulumi.get(self, 'key')
|
key is the label key that the selector applies to.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
key
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter
def key(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'key')
|
@property
@pulumi.getter
def key(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'key')<|docstring|>key is the label key that the selector applies to.<|endoftext|>
|
0c4e49e08176a0283877710e6179293ccac4fbb9a05b090e0d01b0bc406ff63f
|
@property
@pulumi.getter
def operator(self) -> pulumi.Input[str]:
"\n operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist.\n "
return pulumi.get(self, 'operator')
|
operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
operator
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter
def operator(self) -> pulumi.Input[str]:
"\n \n "
return pulumi.get(self, 'operator')
|
@property
@pulumi.getter
def operator(self) -> pulumi.Input[str]:
"\n \n "
return pulumi.get(self, 'operator')<|docstring|>operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist.<|endoftext|>
|
8890282f9ab13c97f11910757bc10d16f9baa2504cd65573fd75ceafa57e1daf
|
@property
@pulumi.getter
def values(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
'\n values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch.\n '
return pulumi.get(self, 'values')
|
values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
values
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter
def values(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
'\n \n '
return pulumi.get(self, 'values')
|
@property
@pulumi.getter
def values(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
'\n \n '
return pulumi.get(self, 'values')<|docstring|>values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch.<|endoftext|>
|
3583cae28aa148b6c7a5ba4dbbbf0664eb1f613ae973b19d42a03d502814d12f
|
def __init__(__self__, *, topology_key: pulumi.Input[str], label_selector: Optional[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorArgs']]=None, namespaces: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]=None):
'\n Defines a set of pods (namely those matching the labelSelector relative to the given namespace(s)) that this pod should be co-located (affinity) or not co-located (anti-affinity) with, where co-located is defined as running on a node whose value of the label with key <topologyKey> matches that of any node on which a pod of the set of pods is running\n :param pulumi.Input[str] topology_key: This pod should be co-located (affinity) or not co-located (anti-affinity) with the pods matching the labelSelector in the specified namespaces, where co-located is defined as running on a node whose value of the label with key topologyKey matches that of any node on which any of the selected pods is running. Empty topologyKey is not allowed.\n :param pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorArgs\'] label_selector: A label query over a set of resources, in this case pods.\n :param pulumi.Input[Sequence[pulumi.Input[str]]] namespaces: namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod\'s namespace"\n '
pulumi.set(__self__, 'topology_key', topology_key)
if (label_selector is not None):
pulumi.set(__self__, 'label_selector', label_selector)
if (namespaces is not None):
pulumi.set(__self__, 'namespaces', namespaces)
|
Defines a set of pods (namely those matching the labelSelector relative to the given namespace(s)) that this pod should be co-located (affinity) or not co-located (anti-affinity) with, where co-located is defined as running on a node whose value of the label with key <topologyKey> matches that of any node on which a pod of the set of pods is running
:param pulumi.Input[str] topology_key: This pod should be co-located (affinity) or not co-located (anti-affinity) with the pods matching the labelSelector in the specified namespaces, where co-located is defined as running on a node whose value of the label with key topologyKey matches that of any node on which any of the selected pods is running. Empty topologyKey is not allowed.
:param pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorArgs'] label_selector: A label query over a set of resources, in this case pods.
:param pulumi.Input[Sequence[pulumi.Input[str]]] namespaces: namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod's namespace"
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
__init__
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
def __init__(__self__, *, topology_key: pulumi.Input[str], label_selector: Optional[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorArgs']]=None, namespaces: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]=None):
'\n Defines a set of pods (namely those matching the labelSelector relative to the given namespace(s)) that this pod should be co-located (affinity) or not co-located (anti-affinity) with, where co-located is defined as running on a node whose value of the label with key <topologyKey> matches that of any node on which a pod of the set of pods is running\n :param pulumi.Input[str] topology_key: This pod should be co-located (affinity) or not co-located (anti-affinity) with the pods matching the labelSelector in the specified namespaces, where co-located is defined as running on a node whose value of the label with key topologyKey matches that of any node on which any of the selected pods is running. Empty topologyKey is not allowed.\n :param pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorArgs\'] label_selector: A label query over a set of resources, in this case pods.\n :param pulumi.Input[Sequence[pulumi.Input[str]]] namespaces: namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod\'s namespace"\n '
pulumi.set(__self__, 'topology_key', topology_key)
if (label_selector is not None):
pulumi.set(__self__, 'label_selector', label_selector)
if (namespaces is not None):
pulumi.set(__self__, 'namespaces', namespaces)
|
def __init__(__self__, *, topology_key: pulumi.Input[str], label_selector: Optional[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorArgs']]=None, namespaces: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]=None):
'\n Defines a set of pods (namely those matching the labelSelector relative to the given namespace(s)) that this pod should be co-located (affinity) or not co-located (anti-affinity) with, where co-located is defined as running on a node whose value of the label with key <topologyKey> matches that of any node on which a pod of the set of pods is running\n :param pulumi.Input[str] topology_key: This pod should be co-located (affinity) or not co-located (anti-affinity) with the pods matching the labelSelector in the specified namespaces, where co-located is defined as running on a node whose value of the label with key topologyKey matches that of any node on which any of the selected pods is running. Empty topologyKey is not allowed.\n :param pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorArgs\'] label_selector: A label query over a set of resources, in this case pods.\n :param pulumi.Input[Sequence[pulumi.Input[str]]] namespaces: namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod\'s namespace"\n '
pulumi.set(__self__, 'topology_key', topology_key)
if (label_selector is not None):
pulumi.set(__self__, 'label_selector', label_selector)
if (namespaces is not None):
pulumi.set(__self__, 'namespaces', namespaces)<|docstring|>Defines a set of pods (namely those matching the labelSelector relative to the given namespace(s)) that this pod should be co-located (affinity) or not co-located (anti-affinity) with, where co-located is defined as running on a node whose value of the label with key <topologyKey> matches that of any node on which a pod of the set of pods is running
:param pulumi.Input[str] topology_key: This pod should be co-located (affinity) or not co-located (anti-affinity) with the pods matching the labelSelector in the specified namespaces, where co-located is defined as running on a node whose value of the label with key topologyKey matches that of any node on which any of the selected pods is running. Empty topologyKey is not allowed.
:param pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorArgs'] label_selector: A label query over a set of resources, in this case pods.
:param pulumi.Input[Sequence[pulumi.Input[str]]] namespaces: namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod's namespace"<|endoftext|>
|
1a7fd32bfbac3e1d1c7b3da8ebc96670c998ac5294448293ae6cf957310d8ab3
|
@property
@pulumi.getter(name='topologyKey')
def topology_key(self) -> pulumi.Input[str]:
'\n This pod should be co-located (affinity) or not co-located (anti-affinity) with the pods matching the labelSelector in the specified namespaces, where co-located is defined as running on a node whose value of the label with key topologyKey matches that of any node on which any of the selected pods is running. Empty topologyKey is not allowed.\n '
return pulumi.get(self, 'topology_key')
|
This pod should be co-located (affinity) or not co-located (anti-affinity) with the pods matching the labelSelector in the specified namespaces, where co-located is defined as running on a node whose value of the label with key topologyKey matches that of any node on which any of the selected pods is running. Empty topologyKey is not allowed.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
topology_key
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter(name='topologyKey')
def topology_key(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'topology_key')
|
@property
@pulumi.getter(name='topologyKey')
def topology_key(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'topology_key')<|docstring|>This pod should be co-located (affinity) or not co-located (anti-affinity) with the pods matching the labelSelector in the specified namespaces, where co-located is defined as running on a node whose value of the label with key topologyKey matches that of any node on which any of the selected pods is running. Empty topologyKey is not allowed.<|endoftext|>
|
c8690906f620a9e69cf8261d71105632288110e5367d41f7a998519df5370488
|
@property
@pulumi.getter(name='labelSelector')
def label_selector(self) -> Optional[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorArgs']]:
'\n A label query over a set of resources, in this case pods.\n '
return pulumi.get(self, 'label_selector')
|
A label query over a set of resources, in this case pods.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
label_selector
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter(name='labelSelector')
def label_selector(self) -> Optional[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorArgs']]:
'\n \n '
return pulumi.get(self, 'label_selector')
|
@property
@pulumi.getter(name='labelSelector')
def label_selector(self) -> Optional[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorArgs']]:
'\n \n '
return pulumi.get(self, 'label_selector')<|docstring|>A label query over a set of resources, in this case pods.<|endoftext|>
|
cafaaebd0b2bde715d14eccb6c5349f21790206a44c76155207e11f20235f51a
|
@property
@pulumi.getter
def namespaces(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
'\n namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod\'s namespace"\n '
return pulumi.get(self, 'namespaces')
|
namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod's namespace"
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
namespaces
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter
def namespaces(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
'\n namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod\'s namespace"\n '
return pulumi.get(self, 'namespaces')
|
@property
@pulumi.getter
def namespaces(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
'\n namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod\'s namespace"\n '
return pulumi.get(self, 'namespaces')<|docstring|>namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod's namespace"<|endoftext|>
|
2da373ba6ff5872ba3a92f8f69eeaf9408489d303ee7df8e5f537a3d881eb910
|
def __init__(__self__, *, match_expressions: Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorMatchExpressionsArgs']]]]=None, match_labels: Optional[pulumi.Input[Mapping[(str, pulumi.Input[str])]]]=None):
'\n A label query over a set of resources, in this case pods.\n :param pulumi.Input[Sequence[pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorMatchExpressionsArgs\']]] match_expressions: matchExpressions is a list of label selector requirements. The requirements are ANDed.\n :param pulumi.Input[Mapping[str, pulumi.Input[str]]] match_labels: matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed.\n '
if (match_expressions is not None):
pulumi.set(__self__, 'match_expressions', match_expressions)
if (match_labels is not None):
pulumi.set(__self__, 'match_labels', match_labels)
|
A label query over a set of resources, in this case pods.
:param pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorMatchExpressionsArgs']]] match_expressions: matchExpressions is a list of label selector requirements. The requirements are ANDed.
:param pulumi.Input[Mapping[str, pulumi.Input[str]]] match_labels: matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
__init__
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
def __init__(__self__, *, match_expressions: Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorMatchExpressionsArgs']]]]=None, match_labels: Optional[pulumi.Input[Mapping[(str, pulumi.Input[str])]]]=None):
'\n A label query over a set of resources, in this case pods.\n :param pulumi.Input[Sequence[pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorMatchExpressionsArgs\']]] match_expressions: matchExpressions is a list of label selector requirements. The requirements are ANDed.\n :param pulumi.Input[Mapping[str, pulumi.Input[str]]] match_labels: matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed.\n '
if (match_expressions is not None):
pulumi.set(__self__, 'match_expressions', match_expressions)
if (match_labels is not None):
pulumi.set(__self__, 'match_labels', match_labels)
|
def __init__(__self__, *, match_expressions: Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorMatchExpressionsArgs']]]]=None, match_labels: Optional[pulumi.Input[Mapping[(str, pulumi.Input[str])]]]=None):
'\n A label query over a set of resources, in this case pods.\n :param pulumi.Input[Sequence[pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorMatchExpressionsArgs\']]] match_expressions: matchExpressions is a list of label selector requirements. The requirements are ANDed.\n :param pulumi.Input[Mapping[str, pulumi.Input[str]]] match_labels: matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed.\n '
if (match_expressions is not None):
pulumi.set(__self__, 'match_expressions', match_expressions)
if (match_labels is not None):
pulumi.set(__self__, 'match_labels', match_labels)<|docstring|>A label query over a set of resources, in this case pods.
:param pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorMatchExpressionsArgs']]] match_expressions: matchExpressions is a list of label selector requirements. The requirements are ANDed.
:param pulumi.Input[Mapping[str, pulumi.Input[str]]] match_labels: matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed.<|endoftext|>
|
819b8b54560bba6298723276bb087c7cfc45550e150aa5bdc3c6272d07b28c27
|
@property
@pulumi.getter(name='matchExpressions')
def match_expressions(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorMatchExpressionsArgs']]]]:
'\n matchExpressions is a list of label selector requirements. The requirements are ANDed.\n '
return pulumi.get(self, 'match_expressions')
|
matchExpressions is a list of label selector requirements. The requirements are ANDed.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
match_expressions
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter(name='matchExpressions')
def match_expressions(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorMatchExpressionsArgs']]]]:
'\n \n '
return pulumi.get(self, 'match_expressions')
|
@property
@pulumi.getter(name='matchExpressions')
def match_expressions(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorMatchExpressionsArgs']]]]:
'\n \n '
return pulumi.get(self, 'match_expressions')<|docstring|>matchExpressions is a list of label selector requirements. The requirements are ANDed.<|endoftext|>
|
c8d28c22c7664eea6a56b076ef07546eb4ceb965de2e9c944999569f79409a76
|
@property
@pulumi.getter(name='matchLabels')
def match_labels(self) -> Optional[pulumi.Input[Mapping[(str, pulumi.Input[str])]]]:
'\n matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed.\n '
return pulumi.get(self, 'match_labels')
|
matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
match_labels
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter(name='matchLabels')
def match_labels(self) -> Optional[pulumi.Input[Mapping[(str, pulumi.Input[str])]]]:
'\n \n '
return pulumi.get(self, 'match_labels')
|
@property
@pulumi.getter(name='matchLabels')
def match_labels(self) -> Optional[pulumi.Input[Mapping[(str, pulumi.Input[str])]]]:
'\n \n '
return pulumi.get(self, 'match_labels')<|docstring|>matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed.<|endoftext|>
|
c920819fc0b4fc3fe978eacb8fbb8d5f1500cc63d1fed6bf3274b88c2f2ce017
|
def __init__(__self__, *, key: pulumi.Input[str], operator: pulumi.Input[str], values: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]=None):
"\n A label selector requirement is a selector that contains values, a key, and an operator that relates the key and values.\n :param pulumi.Input[str] key: key is the label key that the selector applies to.\n :param pulumi.Input[str] operator: operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist.\n :param pulumi.Input[Sequence[pulumi.Input[str]]] values: values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch.\n "
pulumi.set(__self__, 'key', key)
pulumi.set(__self__, 'operator', operator)
if (values is not None):
pulumi.set(__self__, 'values', values)
|
A label selector requirement is a selector that contains values, a key, and an operator that relates the key and values.
:param pulumi.Input[str] key: key is the label key that the selector applies to.
:param pulumi.Input[str] operator: operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist.
:param pulumi.Input[Sequence[pulumi.Input[str]]] values: values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
__init__
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
def __init__(__self__, *, key: pulumi.Input[str], operator: pulumi.Input[str], values: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]=None):
"\n A label selector requirement is a selector that contains values, a key, and an operator that relates the key and values.\n :param pulumi.Input[str] key: key is the label key that the selector applies to.\n :param pulumi.Input[str] operator: operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist.\n :param pulumi.Input[Sequence[pulumi.Input[str]]] values: values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch.\n "
pulumi.set(__self__, 'key', key)
pulumi.set(__self__, 'operator', operator)
if (values is not None):
pulumi.set(__self__, 'values', values)
|
def __init__(__self__, *, key: pulumi.Input[str], operator: pulumi.Input[str], values: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]=None):
"\n A label selector requirement is a selector that contains values, a key, and an operator that relates the key and values.\n :param pulumi.Input[str] key: key is the label key that the selector applies to.\n :param pulumi.Input[str] operator: operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist.\n :param pulumi.Input[Sequence[pulumi.Input[str]]] values: values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch.\n "
pulumi.set(__self__, 'key', key)
pulumi.set(__self__, 'operator', operator)
if (values is not None):
pulumi.set(__self__, 'values', values)<|docstring|>A label selector requirement is a selector that contains values, a key, and an operator that relates the key and values.
:param pulumi.Input[str] key: key is the label key that the selector applies to.
:param pulumi.Input[str] operator: operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist.
:param pulumi.Input[Sequence[pulumi.Input[str]]] values: values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch.<|endoftext|>
|
873b01de6c7b4b390af7286e21dc936c9a738bde5f172c97010521d8ead34b94
|
@property
@pulumi.getter
def key(self) -> pulumi.Input[str]:
'\n key is the label key that the selector applies to.\n '
return pulumi.get(self, 'key')
|
key is the label key that the selector applies to.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
key
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter
def key(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'key')
|
@property
@pulumi.getter
def key(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'key')<|docstring|>key is the label key that the selector applies to.<|endoftext|>
|
0c4e49e08176a0283877710e6179293ccac4fbb9a05b090e0d01b0bc406ff63f
|
@property
@pulumi.getter
def operator(self) -> pulumi.Input[str]:
"\n operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist.\n "
return pulumi.get(self, 'operator')
|
operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
operator
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter
def operator(self) -> pulumi.Input[str]:
"\n \n "
return pulumi.get(self, 'operator')
|
@property
@pulumi.getter
def operator(self) -> pulumi.Input[str]:
"\n \n "
return pulumi.get(self, 'operator')<|docstring|>operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist.<|endoftext|>
|
8890282f9ab13c97f11910757bc10d16f9baa2504cd65573fd75ceafa57e1daf
|
@property
@pulumi.getter
def values(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
'\n values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch.\n '
return pulumi.get(self, 'values')
|
values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
values
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter
def values(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
'\n \n '
return pulumi.get(self, 'values')
|
@property
@pulumi.getter
def values(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
'\n \n '
return pulumi.get(self, 'values')<|docstring|>values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch.<|endoftext|>
|
adbbfbe2fc9bd80658860a8b45b0220560ead0893f98c3f57a489f97ce1ba563
|
def __init__(__self__, *, preferred_during_scheduling_ignored_during_execution: Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionArgs']]]]=None, required_during_scheduling_ignored_during_execution: Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionArgs']]]]=None):
'\n Describes pod anti-affinity scheduling rules (e.g. avoid putting this pod in the same node, zone, etc. as some other pod(s)).\n :param pulumi.Input[Sequence[pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionArgs\']]] preferred_during_scheduling_ignored_during_execution: The scheduler will prefer to schedule pods to nodes that satisfy the anti-affinity expressions specified by this field, but it may choose a node that violates one or more of the expressions. The node that is most preferred is the one with the greatest sum of weights, i.e. for each node that meets all of the scheduling requirements (resource request, requiredDuringScheduling anti-affinity expressions, etc.), compute a sum by iterating through the elements of this field and adding "weight" to the sum if the node has pods which matches the corresponding podAffinityTerm; the node(s) with the highest sum are the most preferred.\n :param pulumi.Input[Sequence[pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionArgs\']]] required_during_scheduling_ignored_during_execution: If the anti-affinity requirements specified by this field are not met at scheduling time, the pod will not be scheduled onto the node. If the anti-affinity requirements specified by this field cease to be met at some point during pod execution (e.g. due to a pod label update), the system may or may not try to eventually evict the pod from its node. When there are multiple elements, the lists of nodes corresponding to each podAffinityTerm are intersected, i.e. all terms must be satisfied.\n '
if (preferred_during_scheduling_ignored_during_execution is not None):
pulumi.set(__self__, 'preferred_during_scheduling_ignored_during_execution', preferred_during_scheduling_ignored_during_execution)
if (required_during_scheduling_ignored_during_execution is not None):
pulumi.set(__self__, 'required_during_scheduling_ignored_during_execution', required_during_scheduling_ignored_during_execution)
|
Describes pod anti-affinity scheduling rules (e.g. avoid putting this pod in the same node, zone, etc. as some other pod(s)).
:param pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionArgs']]] preferred_during_scheduling_ignored_during_execution: The scheduler will prefer to schedule pods to nodes that satisfy the anti-affinity expressions specified by this field, but it may choose a node that violates one or more of the expressions. The node that is most preferred is the one with the greatest sum of weights, i.e. for each node that meets all of the scheduling requirements (resource request, requiredDuringScheduling anti-affinity expressions, etc.), compute a sum by iterating through the elements of this field and adding "weight" to the sum if the node has pods which matches the corresponding podAffinityTerm; the node(s) with the highest sum are the most preferred.
:param pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionArgs']]] required_during_scheduling_ignored_during_execution: If the anti-affinity requirements specified by this field are not met at scheduling time, the pod will not be scheduled onto the node. If the anti-affinity requirements specified by this field cease to be met at some point during pod execution (e.g. due to a pod label update), the system may or may not try to eventually evict the pod from its node. When there are multiple elements, the lists of nodes corresponding to each podAffinityTerm are intersected, i.e. all terms must be satisfied.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
__init__
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
def __init__(__self__, *, preferred_during_scheduling_ignored_during_execution: Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionArgs']]]]=None, required_during_scheduling_ignored_during_execution: Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionArgs']]]]=None):
'\n Describes pod anti-affinity scheduling rules (e.g. avoid putting this pod in the same node, zone, etc. as some other pod(s)).\n :param pulumi.Input[Sequence[pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionArgs\']]] preferred_during_scheduling_ignored_during_execution: The scheduler will prefer to schedule pods to nodes that satisfy the anti-affinity expressions specified by this field, but it may choose a node that violates one or more of the expressions. The node that is most preferred is the one with the greatest sum of weights, i.e. for each node that meets all of the scheduling requirements (resource request, requiredDuringScheduling anti-affinity expressions, etc.), compute a sum by iterating through the elements of this field and adding "weight" to the sum if the node has pods which matches the corresponding podAffinityTerm; the node(s) with the highest sum are the most preferred.\n :param pulumi.Input[Sequence[pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionArgs\']]] required_during_scheduling_ignored_during_execution: If the anti-affinity requirements specified by this field are not met at scheduling time, the pod will not be scheduled onto the node. If the anti-affinity requirements specified by this field cease to be met at some point during pod execution (e.g. due to a pod label update), the system may or may not try to eventually evict the pod from its node. When there are multiple elements, the lists of nodes corresponding to each podAffinityTerm are intersected, i.e. all terms must be satisfied.\n '
if (preferred_during_scheduling_ignored_during_execution is not None):
pulumi.set(__self__, 'preferred_during_scheduling_ignored_during_execution', preferred_during_scheduling_ignored_during_execution)
if (required_during_scheduling_ignored_during_execution is not None):
pulumi.set(__self__, 'required_during_scheduling_ignored_during_execution', required_during_scheduling_ignored_during_execution)
|
def __init__(__self__, *, preferred_during_scheduling_ignored_during_execution: Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionArgs']]]]=None, required_during_scheduling_ignored_during_execution: Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionArgs']]]]=None):
'\n Describes pod anti-affinity scheduling rules (e.g. avoid putting this pod in the same node, zone, etc. as some other pod(s)).\n :param pulumi.Input[Sequence[pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionArgs\']]] preferred_during_scheduling_ignored_during_execution: The scheduler will prefer to schedule pods to nodes that satisfy the anti-affinity expressions specified by this field, but it may choose a node that violates one or more of the expressions. The node that is most preferred is the one with the greatest sum of weights, i.e. for each node that meets all of the scheduling requirements (resource request, requiredDuringScheduling anti-affinity expressions, etc.), compute a sum by iterating through the elements of this field and adding "weight" to the sum if the node has pods which matches the corresponding podAffinityTerm; the node(s) with the highest sum are the most preferred.\n :param pulumi.Input[Sequence[pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionArgs\']]] required_during_scheduling_ignored_during_execution: If the anti-affinity requirements specified by this field are not met at scheduling time, the pod will not be scheduled onto the node. If the anti-affinity requirements specified by this field cease to be met at some point during pod execution (e.g. due to a pod label update), the system may or may not try to eventually evict the pod from its node. When there are multiple elements, the lists of nodes corresponding to each podAffinityTerm are intersected, i.e. all terms must be satisfied.\n '
if (preferred_during_scheduling_ignored_during_execution is not None):
pulumi.set(__self__, 'preferred_during_scheduling_ignored_during_execution', preferred_during_scheduling_ignored_during_execution)
if (required_during_scheduling_ignored_during_execution is not None):
pulumi.set(__self__, 'required_during_scheduling_ignored_during_execution', required_during_scheduling_ignored_during_execution)<|docstring|>Describes pod anti-affinity scheduling rules (e.g. avoid putting this pod in the same node, zone, etc. as some other pod(s)).
:param pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionArgs']]] preferred_during_scheduling_ignored_during_execution: The scheduler will prefer to schedule pods to nodes that satisfy the anti-affinity expressions specified by this field, but it may choose a node that violates one or more of the expressions. The node that is most preferred is the one with the greatest sum of weights, i.e. for each node that meets all of the scheduling requirements (resource request, requiredDuringScheduling anti-affinity expressions, etc.), compute a sum by iterating through the elements of this field and adding "weight" to the sum if the node has pods which matches the corresponding podAffinityTerm; the node(s) with the highest sum are the most preferred.
:param pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionArgs']]] required_during_scheduling_ignored_during_execution: If the anti-affinity requirements specified by this field are not met at scheduling time, the pod will not be scheduled onto the node. If the anti-affinity requirements specified by this field cease to be met at some point during pod execution (e.g. due to a pod label update), the system may or may not try to eventually evict the pod from its node. When there are multiple elements, the lists of nodes corresponding to each podAffinityTerm are intersected, i.e. all terms must be satisfied.<|endoftext|>
|
7575258af588226f6ef672d376c9683ec61f3c038ae42ce50a68f7260aac333b
|
@property
@pulumi.getter(name='preferredDuringSchedulingIgnoredDuringExecution')
def preferred_during_scheduling_ignored_during_execution(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionArgs']]]]:
'\n The scheduler will prefer to schedule pods to nodes that satisfy the anti-affinity expressions specified by this field, but it may choose a node that violates one or more of the expressions. The node that is most preferred is the one with the greatest sum of weights, i.e. for each node that meets all of the scheduling requirements (resource request, requiredDuringScheduling anti-affinity expressions, etc.), compute a sum by iterating through the elements of this field and adding "weight" to the sum if the node has pods which matches the corresponding podAffinityTerm; the node(s) with the highest sum are the most preferred.\n '
return pulumi.get(self, 'preferred_during_scheduling_ignored_during_execution')
|
The scheduler will prefer to schedule pods to nodes that satisfy the anti-affinity expressions specified by this field, but it may choose a node that violates one or more of the expressions. The node that is most preferred is the one with the greatest sum of weights, i.e. for each node that meets all of the scheduling requirements (resource request, requiredDuringScheduling anti-affinity expressions, etc.), compute a sum by iterating through the elements of this field and adding "weight" to the sum if the node has pods which matches the corresponding podAffinityTerm; the node(s) with the highest sum are the most preferred.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
preferred_during_scheduling_ignored_during_execution
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter(name='preferredDuringSchedulingIgnoredDuringExecution')
def preferred_during_scheduling_ignored_during_execution(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionArgs']]]]:
'\n \n '
return pulumi.get(self, 'preferred_during_scheduling_ignored_during_execution')
|
@property
@pulumi.getter(name='preferredDuringSchedulingIgnoredDuringExecution')
def preferred_during_scheduling_ignored_during_execution(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionArgs']]]]:
'\n \n '
return pulumi.get(self, 'preferred_during_scheduling_ignored_during_execution')<|docstring|>The scheduler will prefer to schedule pods to nodes that satisfy the anti-affinity expressions specified by this field, but it may choose a node that violates one or more of the expressions. The node that is most preferred is the one with the greatest sum of weights, i.e. for each node that meets all of the scheduling requirements (resource request, requiredDuringScheduling anti-affinity expressions, etc.), compute a sum by iterating through the elements of this field and adding "weight" to the sum if the node has pods which matches the corresponding podAffinityTerm; the node(s) with the highest sum are the most preferred.<|endoftext|>
|
5c1146b48c150ec9fb8928a34af3a2bca87a23bb4929b7ca8d2a390637320a34
|
@property
@pulumi.getter(name='requiredDuringSchedulingIgnoredDuringExecution')
def required_during_scheduling_ignored_during_execution(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionArgs']]]]:
'\n If the anti-affinity requirements specified by this field are not met at scheduling time, the pod will not be scheduled onto the node. If the anti-affinity requirements specified by this field cease to be met at some point during pod execution (e.g. due to a pod label update), the system may or may not try to eventually evict the pod from its node. When there are multiple elements, the lists of nodes corresponding to each podAffinityTerm are intersected, i.e. all terms must be satisfied.\n '
return pulumi.get(self, 'required_during_scheduling_ignored_during_execution')
|
If the anti-affinity requirements specified by this field are not met at scheduling time, the pod will not be scheduled onto the node. If the anti-affinity requirements specified by this field cease to be met at some point during pod execution (e.g. due to a pod label update), the system may or may not try to eventually evict the pod from its node. When there are multiple elements, the lists of nodes corresponding to each podAffinityTerm are intersected, i.e. all terms must be satisfied.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
required_during_scheduling_ignored_during_execution
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter(name='requiredDuringSchedulingIgnoredDuringExecution')
def required_during_scheduling_ignored_during_execution(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionArgs']]]]:
'\n \n '
return pulumi.get(self, 'required_during_scheduling_ignored_during_execution')
|
@property
@pulumi.getter(name='requiredDuringSchedulingIgnoredDuringExecution')
def required_during_scheduling_ignored_during_execution(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionArgs']]]]:
'\n \n '
return pulumi.get(self, 'required_during_scheduling_ignored_during_execution')<|docstring|>If the anti-affinity requirements specified by this field are not met at scheduling time, the pod will not be scheduled onto the node. If the anti-affinity requirements specified by this field cease to be met at some point during pod execution (e.g. due to a pod label update), the system may or may not try to eventually evict the pod from its node. When there are multiple elements, the lists of nodes corresponding to each podAffinityTerm are intersected, i.e. all terms must be satisfied.<|endoftext|>
|
e6e63d85afa1517211f8bd8be14ed4ec9ff00b4be7461b842ad8d37ef9192733
|
def __init__(__self__, *, pod_affinity_term: pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermArgs'], weight: pulumi.Input[int]):
"\n The weights of all of the matched WeightedPodAffinityTerm fields are added per-node to find the most preferred node(s)\n :param pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermArgs'] pod_affinity_term: Required. A pod affinity term, associated with the corresponding weight.\n :param pulumi.Input[int] weight: weight associated with matching the corresponding podAffinityTerm, in the range 1-100.\n "
pulumi.set(__self__, 'pod_affinity_term', pod_affinity_term)
pulumi.set(__self__, 'weight', weight)
|
The weights of all of the matched WeightedPodAffinityTerm fields are added per-node to find the most preferred node(s)
:param pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermArgs'] pod_affinity_term: Required. A pod affinity term, associated with the corresponding weight.
:param pulumi.Input[int] weight: weight associated with matching the corresponding podAffinityTerm, in the range 1-100.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
__init__
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
def __init__(__self__, *, pod_affinity_term: pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermArgs'], weight: pulumi.Input[int]):
"\n The weights of all of the matched WeightedPodAffinityTerm fields are added per-node to find the most preferred node(s)\n :param pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermArgs'] pod_affinity_term: Required. A pod affinity term, associated with the corresponding weight.\n :param pulumi.Input[int] weight: weight associated with matching the corresponding podAffinityTerm, in the range 1-100.\n "
pulumi.set(__self__, 'pod_affinity_term', pod_affinity_term)
pulumi.set(__self__, 'weight', weight)
|
def __init__(__self__, *, pod_affinity_term: pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermArgs'], weight: pulumi.Input[int]):
"\n The weights of all of the matched WeightedPodAffinityTerm fields are added per-node to find the most preferred node(s)\n :param pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermArgs'] pod_affinity_term: Required. A pod affinity term, associated with the corresponding weight.\n :param pulumi.Input[int] weight: weight associated with matching the corresponding podAffinityTerm, in the range 1-100.\n "
pulumi.set(__self__, 'pod_affinity_term', pod_affinity_term)
pulumi.set(__self__, 'weight', weight)<|docstring|>The weights of all of the matched WeightedPodAffinityTerm fields are added per-node to find the most preferred node(s)
:param pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermArgs'] pod_affinity_term: Required. A pod affinity term, associated with the corresponding weight.
:param pulumi.Input[int] weight: weight associated with matching the corresponding podAffinityTerm, in the range 1-100.<|endoftext|>
|
0475de0cf469d11e6db63a719029da0ae408c96ec67ba699235cbb5a1bcc446e
|
@property
@pulumi.getter(name='podAffinityTerm')
def pod_affinity_term(self) -> pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermArgs']:
'\n Required. A pod affinity term, associated with the corresponding weight.\n '
return pulumi.get(self, 'pod_affinity_term')
|
Required. A pod affinity term, associated with the corresponding weight.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
pod_affinity_term
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter(name='podAffinityTerm')
def pod_affinity_term(self) -> pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermArgs']:
'\n \n '
return pulumi.get(self, 'pod_affinity_term')
|
@property
@pulumi.getter(name='podAffinityTerm')
def pod_affinity_term(self) -> pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermArgs']:
'\n \n '
return pulumi.get(self, 'pod_affinity_term')<|docstring|>Required. A pod affinity term, associated with the corresponding weight.<|endoftext|>
|
cbda27b0cdf343ea47c23ff8abbfa8a96b716aaf51975c7c3ed2982e4a3adb2f
|
@property
@pulumi.getter
def weight(self) -> pulumi.Input[int]:
'\n weight associated with matching the corresponding podAffinityTerm, in the range 1-100.\n '
return pulumi.get(self, 'weight')
|
weight associated with matching the corresponding podAffinityTerm, in the range 1-100.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
weight
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter
def weight(self) -> pulumi.Input[int]:
'\n \n '
return pulumi.get(self, 'weight')
|
@property
@pulumi.getter
def weight(self) -> pulumi.Input[int]:
'\n \n '
return pulumi.get(self, 'weight')<|docstring|>weight associated with matching the corresponding podAffinityTerm, in the range 1-100.<|endoftext|>
|
6a78c646cbcbd8eda2aebb7d6aea3faf060c8017dc164b9763f62d1683fbfad2
|
def __init__(__self__, *, topology_key: pulumi.Input[str], label_selector: Optional[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorArgs']]=None, namespaces: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]=None):
'\n Required. A pod affinity term, associated with the corresponding weight.\n :param pulumi.Input[str] topology_key: This pod should be co-located (affinity) or not co-located (anti-affinity) with the pods matching the labelSelector in the specified namespaces, where co-located is defined as running on a node whose value of the label with key topologyKey matches that of any node on which any of the selected pods is running. Empty topologyKey is not allowed.\n :param pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorArgs\'] label_selector: A label query over a set of resources, in this case pods.\n :param pulumi.Input[Sequence[pulumi.Input[str]]] namespaces: namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod\'s namespace"\n '
pulumi.set(__self__, 'topology_key', topology_key)
if (label_selector is not None):
pulumi.set(__self__, 'label_selector', label_selector)
if (namespaces is not None):
pulumi.set(__self__, 'namespaces', namespaces)
|
Required. A pod affinity term, associated with the corresponding weight.
:param pulumi.Input[str] topology_key: This pod should be co-located (affinity) or not co-located (anti-affinity) with the pods matching the labelSelector in the specified namespaces, where co-located is defined as running on a node whose value of the label with key topologyKey matches that of any node on which any of the selected pods is running. Empty topologyKey is not allowed.
:param pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorArgs'] label_selector: A label query over a set of resources, in this case pods.
:param pulumi.Input[Sequence[pulumi.Input[str]]] namespaces: namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod's namespace"
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
__init__
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
def __init__(__self__, *, topology_key: pulumi.Input[str], label_selector: Optional[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorArgs']]=None, namespaces: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]=None):
'\n Required. A pod affinity term, associated with the corresponding weight.\n :param pulumi.Input[str] topology_key: This pod should be co-located (affinity) or not co-located (anti-affinity) with the pods matching the labelSelector in the specified namespaces, where co-located is defined as running on a node whose value of the label with key topologyKey matches that of any node on which any of the selected pods is running. Empty topologyKey is not allowed.\n :param pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorArgs\'] label_selector: A label query over a set of resources, in this case pods.\n :param pulumi.Input[Sequence[pulumi.Input[str]]] namespaces: namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod\'s namespace"\n '
pulumi.set(__self__, 'topology_key', topology_key)
if (label_selector is not None):
pulumi.set(__self__, 'label_selector', label_selector)
if (namespaces is not None):
pulumi.set(__self__, 'namespaces', namespaces)
|
def __init__(__self__, *, topology_key: pulumi.Input[str], label_selector: Optional[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorArgs']]=None, namespaces: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]=None):
'\n Required. A pod affinity term, associated with the corresponding weight.\n :param pulumi.Input[str] topology_key: This pod should be co-located (affinity) or not co-located (anti-affinity) with the pods matching the labelSelector in the specified namespaces, where co-located is defined as running on a node whose value of the label with key topologyKey matches that of any node on which any of the selected pods is running. Empty topologyKey is not allowed.\n :param pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorArgs\'] label_selector: A label query over a set of resources, in this case pods.\n :param pulumi.Input[Sequence[pulumi.Input[str]]] namespaces: namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod\'s namespace"\n '
pulumi.set(__self__, 'topology_key', topology_key)
if (label_selector is not None):
pulumi.set(__self__, 'label_selector', label_selector)
if (namespaces is not None):
pulumi.set(__self__, 'namespaces', namespaces)<|docstring|>Required. A pod affinity term, associated with the corresponding weight.
:param pulumi.Input[str] topology_key: This pod should be co-located (affinity) or not co-located (anti-affinity) with the pods matching the labelSelector in the specified namespaces, where co-located is defined as running on a node whose value of the label with key topologyKey matches that of any node on which any of the selected pods is running. Empty topologyKey is not allowed.
:param pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorArgs'] label_selector: A label query over a set of resources, in this case pods.
:param pulumi.Input[Sequence[pulumi.Input[str]]] namespaces: namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod's namespace"<|endoftext|>
|
1a7fd32bfbac3e1d1c7b3da8ebc96670c998ac5294448293ae6cf957310d8ab3
|
@property
@pulumi.getter(name='topologyKey')
def topology_key(self) -> pulumi.Input[str]:
'\n This pod should be co-located (affinity) or not co-located (anti-affinity) with the pods matching the labelSelector in the specified namespaces, where co-located is defined as running on a node whose value of the label with key topologyKey matches that of any node on which any of the selected pods is running. Empty topologyKey is not allowed.\n '
return pulumi.get(self, 'topology_key')
|
This pod should be co-located (affinity) or not co-located (anti-affinity) with the pods matching the labelSelector in the specified namespaces, where co-located is defined as running on a node whose value of the label with key topologyKey matches that of any node on which any of the selected pods is running. Empty topologyKey is not allowed.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
topology_key
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter(name='topologyKey')
def topology_key(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'topology_key')
|
@property
@pulumi.getter(name='topologyKey')
def topology_key(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'topology_key')<|docstring|>This pod should be co-located (affinity) or not co-located (anti-affinity) with the pods matching the labelSelector in the specified namespaces, where co-located is defined as running on a node whose value of the label with key topologyKey matches that of any node on which any of the selected pods is running. Empty topologyKey is not allowed.<|endoftext|>
|
04de335ddac1ae44b28cacfee3557f4e8ea883a129d1a490749a19b4e706500d
|
@property
@pulumi.getter(name='labelSelector')
def label_selector(self) -> Optional[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorArgs']]:
'\n A label query over a set of resources, in this case pods.\n '
return pulumi.get(self, 'label_selector')
|
A label query over a set of resources, in this case pods.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
label_selector
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter(name='labelSelector')
def label_selector(self) -> Optional[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorArgs']]:
'\n \n '
return pulumi.get(self, 'label_selector')
|
@property
@pulumi.getter(name='labelSelector')
def label_selector(self) -> Optional[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorArgs']]:
'\n \n '
return pulumi.get(self, 'label_selector')<|docstring|>A label query over a set of resources, in this case pods.<|endoftext|>
|
cafaaebd0b2bde715d14eccb6c5349f21790206a44c76155207e11f20235f51a
|
@property
@pulumi.getter
def namespaces(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
'\n namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod\'s namespace"\n '
return pulumi.get(self, 'namespaces')
|
namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod's namespace"
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
namespaces
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter
def namespaces(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
'\n namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod\'s namespace"\n '
return pulumi.get(self, 'namespaces')
|
@property
@pulumi.getter
def namespaces(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
'\n namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod\'s namespace"\n '
return pulumi.get(self, 'namespaces')<|docstring|>namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod's namespace"<|endoftext|>
|
51a800b0e2ffa5ccce37807330db2f1e80b06e1b98ecc81785961dd151d0360f
|
def __init__(__self__, *, match_expressions: Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorMatchExpressionsArgs']]]]=None, match_labels: Optional[pulumi.Input[Mapping[(str, pulumi.Input[str])]]]=None):
'\n A label query over a set of resources, in this case pods.\n :param pulumi.Input[Sequence[pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorMatchExpressionsArgs\']]] match_expressions: matchExpressions is a list of label selector requirements. The requirements are ANDed.\n :param pulumi.Input[Mapping[str, pulumi.Input[str]]] match_labels: matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed.\n '
if (match_expressions is not None):
pulumi.set(__self__, 'match_expressions', match_expressions)
if (match_labels is not None):
pulumi.set(__self__, 'match_labels', match_labels)
|
A label query over a set of resources, in this case pods.
:param pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorMatchExpressionsArgs']]] match_expressions: matchExpressions is a list of label selector requirements. The requirements are ANDed.
:param pulumi.Input[Mapping[str, pulumi.Input[str]]] match_labels: matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
__init__
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
def __init__(__self__, *, match_expressions: Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorMatchExpressionsArgs']]]]=None, match_labels: Optional[pulumi.Input[Mapping[(str, pulumi.Input[str])]]]=None):
'\n A label query over a set of resources, in this case pods.\n :param pulumi.Input[Sequence[pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorMatchExpressionsArgs\']]] match_expressions: matchExpressions is a list of label selector requirements. The requirements are ANDed.\n :param pulumi.Input[Mapping[str, pulumi.Input[str]]] match_labels: matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed.\n '
if (match_expressions is not None):
pulumi.set(__self__, 'match_expressions', match_expressions)
if (match_labels is not None):
pulumi.set(__self__, 'match_labels', match_labels)
|
def __init__(__self__, *, match_expressions: Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorMatchExpressionsArgs']]]]=None, match_labels: Optional[pulumi.Input[Mapping[(str, pulumi.Input[str])]]]=None):
'\n A label query over a set of resources, in this case pods.\n :param pulumi.Input[Sequence[pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorMatchExpressionsArgs\']]] match_expressions: matchExpressions is a list of label selector requirements. The requirements are ANDed.\n :param pulumi.Input[Mapping[str, pulumi.Input[str]]] match_labels: matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed.\n '
if (match_expressions is not None):
pulumi.set(__self__, 'match_expressions', match_expressions)
if (match_labels is not None):
pulumi.set(__self__, 'match_labels', match_labels)<|docstring|>A label query over a set of resources, in this case pods.
:param pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorMatchExpressionsArgs']]] match_expressions: matchExpressions is a list of label selector requirements. The requirements are ANDed.
:param pulumi.Input[Mapping[str, pulumi.Input[str]]] match_labels: matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed.<|endoftext|>
|
886acdf5ca0a2e0c009efe5d93b1aa72689b7b802fcd9c159268ffd73deae4c9
|
@property
@pulumi.getter(name='matchExpressions')
def match_expressions(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorMatchExpressionsArgs']]]]:
'\n matchExpressions is a list of label selector requirements. The requirements are ANDed.\n '
return pulumi.get(self, 'match_expressions')
|
matchExpressions is a list of label selector requirements. The requirements are ANDed.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
match_expressions
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter(name='matchExpressions')
def match_expressions(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorMatchExpressionsArgs']]]]:
'\n \n '
return pulumi.get(self, 'match_expressions')
|
@property
@pulumi.getter(name='matchExpressions')
def match_expressions(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityPreferredDuringSchedulingIgnoredDuringExecutionPodAffinityTermLabelSelectorMatchExpressionsArgs']]]]:
'\n \n '
return pulumi.get(self, 'match_expressions')<|docstring|>matchExpressions is a list of label selector requirements. The requirements are ANDed.<|endoftext|>
|
c8d28c22c7664eea6a56b076ef07546eb4ceb965de2e9c944999569f79409a76
|
@property
@pulumi.getter(name='matchLabels')
def match_labels(self) -> Optional[pulumi.Input[Mapping[(str, pulumi.Input[str])]]]:
'\n matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed.\n '
return pulumi.get(self, 'match_labels')
|
matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
match_labels
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter(name='matchLabels')
def match_labels(self) -> Optional[pulumi.Input[Mapping[(str, pulumi.Input[str])]]]:
'\n \n '
return pulumi.get(self, 'match_labels')
|
@property
@pulumi.getter(name='matchLabels')
def match_labels(self) -> Optional[pulumi.Input[Mapping[(str, pulumi.Input[str])]]]:
'\n \n '
return pulumi.get(self, 'match_labels')<|docstring|>matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed.<|endoftext|>
|
c920819fc0b4fc3fe978eacb8fbb8d5f1500cc63d1fed6bf3274b88c2f2ce017
|
def __init__(__self__, *, key: pulumi.Input[str], operator: pulumi.Input[str], values: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]=None):
"\n A label selector requirement is a selector that contains values, a key, and an operator that relates the key and values.\n :param pulumi.Input[str] key: key is the label key that the selector applies to.\n :param pulumi.Input[str] operator: operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist.\n :param pulumi.Input[Sequence[pulumi.Input[str]]] values: values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch.\n "
pulumi.set(__self__, 'key', key)
pulumi.set(__self__, 'operator', operator)
if (values is not None):
pulumi.set(__self__, 'values', values)
|
A label selector requirement is a selector that contains values, a key, and an operator that relates the key and values.
:param pulumi.Input[str] key: key is the label key that the selector applies to.
:param pulumi.Input[str] operator: operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist.
:param pulumi.Input[Sequence[pulumi.Input[str]]] values: values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
__init__
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
def __init__(__self__, *, key: pulumi.Input[str], operator: pulumi.Input[str], values: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]=None):
"\n A label selector requirement is a selector that contains values, a key, and an operator that relates the key and values.\n :param pulumi.Input[str] key: key is the label key that the selector applies to.\n :param pulumi.Input[str] operator: operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist.\n :param pulumi.Input[Sequence[pulumi.Input[str]]] values: values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch.\n "
pulumi.set(__self__, 'key', key)
pulumi.set(__self__, 'operator', operator)
if (values is not None):
pulumi.set(__self__, 'values', values)
|
def __init__(__self__, *, key: pulumi.Input[str], operator: pulumi.Input[str], values: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]=None):
"\n A label selector requirement is a selector that contains values, a key, and an operator that relates the key and values.\n :param pulumi.Input[str] key: key is the label key that the selector applies to.\n :param pulumi.Input[str] operator: operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist.\n :param pulumi.Input[Sequence[pulumi.Input[str]]] values: values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch.\n "
pulumi.set(__self__, 'key', key)
pulumi.set(__self__, 'operator', operator)
if (values is not None):
pulumi.set(__self__, 'values', values)<|docstring|>A label selector requirement is a selector that contains values, a key, and an operator that relates the key and values.
:param pulumi.Input[str] key: key is the label key that the selector applies to.
:param pulumi.Input[str] operator: operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist.
:param pulumi.Input[Sequence[pulumi.Input[str]]] values: values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch.<|endoftext|>
|
873b01de6c7b4b390af7286e21dc936c9a738bde5f172c97010521d8ead34b94
|
@property
@pulumi.getter
def key(self) -> pulumi.Input[str]:
'\n key is the label key that the selector applies to.\n '
return pulumi.get(self, 'key')
|
key is the label key that the selector applies to.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
key
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter
def key(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'key')
|
@property
@pulumi.getter
def key(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'key')<|docstring|>key is the label key that the selector applies to.<|endoftext|>
|
0c4e49e08176a0283877710e6179293ccac4fbb9a05b090e0d01b0bc406ff63f
|
@property
@pulumi.getter
def operator(self) -> pulumi.Input[str]:
"\n operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist.\n "
return pulumi.get(self, 'operator')
|
operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
operator
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter
def operator(self) -> pulumi.Input[str]:
"\n \n "
return pulumi.get(self, 'operator')
|
@property
@pulumi.getter
def operator(self) -> pulumi.Input[str]:
"\n \n "
return pulumi.get(self, 'operator')<|docstring|>operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist.<|endoftext|>
|
8890282f9ab13c97f11910757bc10d16f9baa2504cd65573fd75ceafa57e1daf
|
@property
@pulumi.getter
def values(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
'\n values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch.\n '
return pulumi.get(self, 'values')
|
values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
values
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter
def values(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
'\n \n '
return pulumi.get(self, 'values')
|
@property
@pulumi.getter
def values(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
'\n \n '
return pulumi.get(self, 'values')<|docstring|>values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch.<|endoftext|>
|
eab227fb83678e98d68eb939c590a18837d1be6e9dfa2dd02d2da6e31e02fe54
|
def __init__(__self__, *, topology_key: pulumi.Input[str], label_selector: Optional[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorArgs']]=None, namespaces: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]=None):
'\n Defines a set of pods (namely those matching the labelSelector relative to the given namespace(s)) that this pod should be co-located (affinity) or not co-located (anti-affinity) with, where co-located is defined as running on a node whose value of the label with key <topologyKey> matches that of any node on which a pod of the set of pods is running\n :param pulumi.Input[str] topology_key: This pod should be co-located (affinity) or not co-located (anti-affinity) with the pods matching the labelSelector in the specified namespaces, where co-located is defined as running on a node whose value of the label with key topologyKey matches that of any node on which any of the selected pods is running. Empty topologyKey is not allowed.\n :param pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorArgs\'] label_selector: A label query over a set of resources, in this case pods.\n :param pulumi.Input[Sequence[pulumi.Input[str]]] namespaces: namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod\'s namespace"\n '
pulumi.set(__self__, 'topology_key', topology_key)
if (label_selector is not None):
pulumi.set(__self__, 'label_selector', label_selector)
if (namespaces is not None):
pulumi.set(__self__, 'namespaces', namespaces)
|
Defines a set of pods (namely those matching the labelSelector relative to the given namespace(s)) that this pod should be co-located (affinity) or not co-located (anti-affinity) with, where co-located is defined as running on a node whose value of the label with key <topologyKey> matches that of any node on which a pod of the set of pods is running
:param pulumi.Input[str] topology_key: This pod should be co-located (affinity) or not co-located (anti-affinity) with the pods matching the labelSelector in the specified namespaces, where co-located is defined as running on a node whose value of the label with key topologyKey matches that of any node on which any of the selected pods is running. Empty topologyKey is not allowed.
:param pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorArgs'] label_selector: A label query over a set of resources, in this case pods.
:param pulumi.Input[Sequence[pulumi.Input[str]]] namespaces: namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod's namespace"
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
__init__
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
def __init__(__self__, *, topology_key: pulumi.Input[str], label_selector: Optional[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorArgs']]=None, namespaces: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]=None):
'\n Defines a set of pods (namely those matching the labelSelector relative to the given namespace(s)) that this pod should be co-located (affinity) or not co-located (anti-affinity) with, where co-located is defined as running on a node whose value of the label with key <topologyKey> matches that of any node on which a pod of the set of pods is running\n :param pulumi.Input[str] topology_key: This pod should be co-located (affinity) or not co-located (anti-affinity) with the pods matching the labelSelector in the specified namespaces, where co-located is defined as running on a node whose value of the label with key topologyKey matches that of any node on which any of the selected pods is running. Empty topologyKey is not allowed.\n :param pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorArgs\'] label_selector: A label query over a set of resources, in this case pods.\n :param pulumi.Input[Sequence[pulumi.Input[str]]] namespaces: namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod\'s namespace"\n '
pulumi.set(__self__, 'topology_key', topology_key)
if (label_selector is not None):
pulumi.set(__self__, 'label_selector', label_selector)
if (namespaces is not None):
pulumi.set(__self__, 'namespaces', namespaces)
|
def __init__(__self__, *, topology_key: pulumi.Input[str], label_selector: Optional[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorArgs']]=None, namespaces: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]=None):
'\n Defines a set of pods (namely those matching the labelSelector relative to the given namespace(s)) that this pod should be co-located (affinity) or not co-located (anti-affinity) with, where co-located is defined as running on a node whose value of the label with key <topologyKey> matches that of any node on which a pod of the set of pods is running\n :param pulumi.Input[str] topology_key: This pod should be co-located (affinity) or not co-located (anti-affinity) with the pods matching the labelSelector in the specified namespaces, where co-located is defined as running on a node whose value of the label with key topologyKey matches that of any node on which any of the selected pods is running. Empty topologyKey is not allowed.\n :param pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorArgs\'] label_selector: A label query over a set of resources, in this case pods.\n :param pulumi.Input[Sequence[pulumi.Input[str]]] namespaces: namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod\'s namespace"\n '
pulumi.set(__self__, 'topology_key', topology_key)
if (label_selector is not None):
pulumi.set(__self__, 'label_selector', label_selector)
if (namespaces is not None):
pulumi.set(__self__, 'namespaces', namespaces)<|docstring|>Defines a set of pods (namely those matching the labelSelector relative to the given namespace(s)) that this pod should be co-located (affinity) or not co-located (anti-affinity) with, where co-located is defined as running on a node whose value of the label with key <topologyKey> matches that of any node on which a pod of the set of pods is running
:param pulumi.Input[str] topology_key: This pod should be co-located (affinity) or not co-located (anti-affinity) with the pods matching the labelSelector in the specified namespaces, where co-located is defined as running on a node whose value of the label with key topologyKey matches that of any node on which any of the selected pods is running. Empty topologyKey is not allowed.
:param pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorArgs'] label_selector: A label query over a set of resources, in this case pods.
:param pulumi.Input[Sequence[pulumi.Input[str]]] namespaces: namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod's namespace"<|endoftext|>
|
1a7fd32bfbac3e1d1c7b3da8ebc96670c998ac5294448293ae6cf957310d8ab3
|
@property
@pulumi.getter(name='topologyKey')
def topology_key(self) -> pulumi.Input[str]:
'\n This pod should be co-located (affinity) or not co-located (anti-affinity) with the pods matching the labelSelector in the specified namespaces, where co-located is defined as running on a node whose value of the label with key topologyKey matches that of any node on which any of the selected pods is running. Empty topologyKey is not allowed.\n '
return pulumi.get(self, 'topology_key')
|
This pod should be co-located (affinity) or not co-located (anti-affinity) with the pods matching the labelSelector in the specified namespaces, where co-located is defined as running on a node whose value of the label with key topologyKey matches that of any node on which any of the selected pods is running. Empty topologyKey is not allowed.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
topology_key
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter(name='topologyKey')
def topology_key(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'topology_key')
|
@property
@pulumi.getter(name='topologyKey')
def topology_key(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'topology_key')<|docstring|>This pod should be co-located (affinity) or not co-located (anti-affinity) with the pods matching the labelSelector in the specified namespaces, where co-located is defined as running on a node whose value of the label with key topologyKey matches that of any node on which any of the selected pods is running. Empty topologyKey is not allowed.<|endoftext|>
|
65e00caed452f14bbf473cde43911b9d4cacbf1e448d70b263f16faecd91378c
|
@property
@pulumi.getter(name='labelSelector')
def label_selector(self) -> Optional[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorArgs']]:
'\n A label query over a set of resources, in this case pods.\n '
return pulumi.get(self, 'label_selector')
|
A label query over a set of resources, in this case pods.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
label_selector
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter(name='labelSelector')
def label_selector(self) -> Optional[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorArgs']]:
'\n \n '
return pulumi.get(self, 'label_selector')
|
@property
@pulumi.getter(name='labelSelector')
def label_selector(self) -> Optional[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorArgs']]:
'\n \n '
return pulumi.get(self, 'label_selector')<|docstring|>A label query over a set of resources, in this case pods.<|endoftext|>
|
cafaaebd0b2bde715d14eccb6c5349f21790206a44c76155207e11f20235f51a
|
@property
@pulumi.getter
def namespaces(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
'\n namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod\'s namespace"\n '
return pulumi.get(self, 'namespaces')
|
namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod's namespace"
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
namespaces
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter
def namespaces(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
'\n namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod\'s namespace"\n '
return pulumi.get(self, 'namespaces')
|
@property
@pulumi.getter
def namespaces(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
'\n namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod\'s namespace"\n '
return pulumi.get(self, 'namespaces')<|docstring|>namespaces specifies which namespaces the labelSelector applies to (matches against); null or empty list means "this pod's namespace"<|endoftext|>
|
fa1feea552b72930b93955053e336bb1aab037767350442d7d0ab50ba9d82fe2
|
def __init__(__self__, *, match_expressions: Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorMatchExpressionsArgs']]]]=None, match_labels: Optional[pulumi.Input[Mapping[(str, pulumi.Input[str])]]]=None):
'\n A label query over a set of resources, in this case pods.\n :param pulumi.Input[Sequence[pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorMatchExpressionsArgs\']]] match_expressions: matchExpressions is a list of label selector requirements. The requirements are ANDed.\n :param pulumi.Input[Mapping[str, pulumi.Input[str]]] match_labels: matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed.\n '
if (match_expressions is not None):
pulumi.set(__self__, 'match_expressions', match_expressions)
if (match_labels is not None):
pulumi.set(__self__, 'match_labels', match_labels)
|
A label query over a set of resources, in this case pods.
:param pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorMatchExpressionsArgs']]] match_expressions: matchExpressions is a list of label selector requirements. The requirements are ANDed.
:param pulumi.Input[Mapping[str, pulumi.Input[str]]] match_labels: matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
__init__
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
def __init__(__self__, *, match_expressions: Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorMatchExpressionsArgs']]]]=None, match_labels: Optional[pulumi.Input[Mapping[(str, pulumi.Input[str])]]]=None):
'\n A label query over a set of resources, in this case pods.\n :param pulumi.Input[Sequence[pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorMatchExpressionsArgs\']]] match_expressions: matchExpressions is a list of label selector requirements. The requirements are ANDed.\n :param pulumi.Input[Mapping[str, pulumi.Input[str]]] match_labels: matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed.\n '
if (match_expressions is not None):
pulumi.set(__self__, 'match_expressions', match_expressions)
if (match_labels is not None):
pulumi.set(__self__, 'match_labels', match_labels)
|
def __init__(__self__, *, match_expressions: Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorMatchExpressionsArgs']]]]=None, match_labels: Optional[pulumi.Input[Mapping[(str, pulumi.Input[str])]]]=None):
'\n A label query over a set of resources, in this case pods.\n :param pulumi.Input[Sequence[pulumi.Input[\'IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorMatchExpressionsArgs\']]] match_expressions: matchExpressions is a list of label selector requirements. The requirements are ANDed.\n :param pulumi.Input[Mapping[str, pulumi.Input[str]]] match_labels: matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed.\n '
if (match_expressions is not None):
pulumi.set(__self__, 'match_expressions', match_expressions)
if (match_labels is not None):
pulumi.set(__self__, 'match_labels', match_labels)<|docstring|>A label query over a set of resources, in this case pods.
:param pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorMatchExpressionsArgs']]] match_expressions: matchExpressions is a list of label selector requirements. The requirements are ANDed.
:param pulumi.Input[Mapping[str, pulumi.Input[str]]] match_labels: matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed.<|endoftext|>
|
5c7e1d947682c5bdbf7b53e6b0119c6fcd145037f32f31354316460da8ef6b45
|
@property
@pulumi.getter(name='matchExpressions')
def match_expressions(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorMatchExpressionsArgs']]]]:
'\n matchExpressions is a list of label selector requirements. The requirements are ANDed.\n '
return pulumi.get(self, 'match_expressions')
|
matchExpressions is a list of label selector requirements. The requirements are ANDed.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
match_expressions
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter(name='matchExpressions')
def match_expressions(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorMatchExpressionsArgs']]]]:
'\n \n '
return pulumi.get(self, 'match_expressions')
|
@property
@pulumi.getter(name='matchExpressions')
def match_expressions(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['IBMBlockCSISpecNodeAffinityPodAntiAffinityRequiredDuringSchedulingIgnoredDuringExecutionLabelSelectorMatchExpressionsArgs']]]]:
'\n \n '
return pulumi.get(self, 'match_expressions')<|docstring|>matchExpressions is a list of label selector requirements. The requirements are ANDed.<|endoftext|>
|
c8d28c22c7664eea6a56b076ef07546eb4ceb965de2e9c944999569f79409a76
|
@property
@pulumi.getter(name='matchLabels')
def match_labels(self) -> Optional[pulumi.Input[Mapping[(str, pulumi.Input[str])]]]:
'\n matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed.\n '
return pulumi.get(self, 'match_labels')
|
matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
match_labels
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter(name='matchLabels')
def match_labels(self) -> Optional[pulumi.Input[Mapping[(str, pulumi.Input[str])]]]:
'\n \n '
return pulumi.get(self, 'match_labels')
|
@property
@pulumi.getter(name='matchLabels')
def match_labels(self) -> Optional[pulumi.Input[Mapping[(str, pulumi.Input[str])]]]:
'\n \n '
return pulumi.get(self, 'match_labels')<|docstring|>matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed.<|endoftext|>
|
c920819fc0b4fc3fe978eacb8fbb8d5f1500cc63d1fed6bf3274b88c2f2ce017
|
def __init__(__self__, *, key: pulumi.Input[str], operator: pulumi.Input[str], values: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]=None):
"\n A label selector requirement is a selector that contains values, a key, and an operator that relates the key and values.\n :param pulumi.Input[str] key: key is the label key that the selector applies to.\n :param pulumi.Input[str] operator: operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist.\n :param pulumi.Input[Sequence[pulumi.Input[str]]] values: values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch.\n "
pulumi.set(__self__, 'key', key)
pulumi.set(__self__, 'operator', operator)
if (values is not None):
pulumi.set(__self__, 'values', values)
|
A label selector requirement is a selector that contains values, a key, and an operator that relates the key and values.
:param pulumi.Input[str] key: key is the label key that the selector applies to.
:param pulumi.Input[str] operator: operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist.
:param pulumi.Input[Sequence[pulumi.Input[str]]] values: values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
__init__
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
def __init__(__self__, *, key: pulumi.Input[str], operator: pulumi.Input[str], values: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]=None):
"\n A label selector requirement is a selector that contains values, a key, and an operator that relates the key and values.\n :param pulumi.Input[str] key: key is the label key that the selector applies to.\n :param pulumi.Input[str] operator: operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist.\n :param pulumi.Input[Sequence[pulumi.Input[str]]] values: values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch.\n "
pulumi.set(__self__, 'key', key)
pulumi.set(__self__, 'operator', operator)
if (values is not None):
pulumi.set(__self__, 'values', values)
|
def __init__(__self__, *, key: pulumi.Input[str], operator: pulumi.Input[str], values: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]=None):
"\n A label selector requirement is a selector that contains values, a key, and an operator that relates the key and values.\n :param pulumi.Input[str] key: key is the label key that the selector applies to.\n :param pulumi.Input[str] operator: operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist.\n :param pulumi.Input[Sequence[pulumi.Input[str]]] values: values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch.\n "
pulumi.set(__self__, 'key', key)
pulumi.set(__self__, 'operator', operator)
if (values is not None):
pulumi.set(__self__, 'values', values)<|docstring|>A label selector requirement is a selector that contains values, a key, and an operator that relates the key and values.
:param pulumi.Input[str] key: key is the label key that the selector applies to.
:param pulumi.Input[str] operator: operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist.
:param pulumi.Input[Sequence[pulumi.Input[str]]] values: values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch.<|endoftext|>
|
873b01de6c7b4b390af7286e21dc936c9a738bde5f172c97010521d8ead34b94
|
@property
@pulumi.getter
def key(self) -> pulumi.Input[str]:
'\n key is the label key that the selector applies to.\n '
return pulumi.get(self, 'key')
|
key is the label key that the selector applies to.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
key
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter
def key(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'key')
|
@property
@pulumi.getter
def key(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'key')<|docstring|>key is the label key that the selector applies to.<|endoftext|>
|
0c4e49e08176a0283877710e6179293ccac4fbb9a05b090e0d01b0bc406ff63f
|
@property
@pulumi.getter
def operator(self) -> pulumi.Input[str]:
"\n operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist.\n "
return pulumi.get(self, 'operator')
|
operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
operator
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter
def operator(self) -> pulumi.Input[str]:
"\n \n "
return pulumi.get(self, 'operator')
|
@property
@pulumi.getter
def operator(self) -> pulumi.Input[str]:
"\n \n "
return pulumi.get(self, 'operator')<|docstring|>operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist.<|endoftext|>
|
8890282f9ab13c97f11910757bc10d16f9baa2504cd65573fd75ceafa57e1daf
|
@property
@pulumi.getter
def values(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
'\n values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch.\n '
return pulumi.get(self, 'values')
|
values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
values
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter
def values(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
'\n \n '
return pulumi.get(self, 'values')
|
@property
@pulumi.getter
def values(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
'\n \n '
return pulumi.get(self, 'values')<|docstring|>values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch.<|endoftext|>
|
792282a676c40c879cfb934a9fbf7817889dade407a6d6ec03318c357d63111d
|
def __init__(__self__, *, effect: Optional[pulumi.Input[str]]=None, key: Optional[pulumi.Input[str]]=None, operator: Optional[pulumi.Input[str]]=None, toleration_seconds: Optional[pulumi.Input[int]]=None, value: Optional[pulumi.Input[str]]=None):
"\n The pod this Toleration is attached to tolerates any taint that matches the triple <key,value,effect> using the matching operator <operator>.\n :param pulumi.Input[str] effect: Effect indicates the taint effect to match. Empty means match all taint effects. When specified, allowed values are NoSchedule, PreferNoSchedule and NoExecute.\n :param pulumi.Input[str] key: Key is the taint key that the toleration applies to. Empty means match all taint keys. If the key is empty, operator must be Exists; this combination means to match all values and all keys.\n :param pulumi.Input[str] operator: Operator represents a key's relationship to the value. Valid operators are Exists and Equal. Defaults to Equal. Exists is equivalent to wildcard for value, so that a pod can tolerate all taints of a particular category.\n :param pulumi.Input[int] toleration_seconds: TolerationSeconds represents the period of time the toleration (which must be of effect NoExecute, otherwise this field is ignored) tolerates the taint. By default, it is not set, which means tolerate the taint forever (do not evict). Zero and negative values will be treated as 0 (evict immediately) by the system.\n :param pulumi.Input[str] value: Value is the taint value the toleration matches to. If the operator is Exists, the value should be empty, otherwise just a regular string.\n "
if (effect is not None):
pulumi.set(__self__, 'effect', effect)
if (key is not None):
pulumi.set(__self__, 'key', key)
if (operator is not None):
pulumi.set(__self__, 'operator', operator)
if (toleration_seconds is not None):
pulumi.set(__self__, 'toleration_seconds', toleration_seconds)
if (value is not None):
pulumi.set(__self__, 'value', value)
|
The pod this Toleration is attached to tolerates any taint that matches the triple <key,value,effect> using the matching operator <operator>.
:param pulumi.Input[str] effect: Effect indicates the taint effect to match. Empty means match all taint effects. When specified, allowed values are NoSchedule, PreferNoSchedule and NoExecute.
:param pulumi.Input[str] key: Key is the taint key that the toleration applies to. Empty means match all taint keys. If the key is empty, operator must be Exists; this combination means to match all values and all keys.
:param pulumi.Input[str] operator: Operator represents a key's relationship to the value. Valid operators are Exists and Equal. Defaults to Equal. Exists is equivalent to wildcard for value, so that a pod can tolerate all taints of a particular category.
:param pulumi.Input[int] toleration_seconds: TolerationSeconds represents the period of time the toleration (which must be of effect NoExecute, otherwise this field is ignored) tolerates the taint. By default, it is not set, which means tolerate the taint forever (do not evict). Zero and negative values will be treated as 0 (evict immediately) by the system.
:param pulumi.Input[str] value: Value is the taint value the toleration matches to. If the operator is Exists, the value should be empty, otherwise just a regular string.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
__init__
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
def __init__(__self__, *, effect: Optional[pulumi.Input[str]]=None, key: Optional[pulumi.Input[str]]=None, operator: Optional[pulumi.Input[str]]=None, toleration_seconds: Optional[pulumi.Input[int]]=None, value: Optional[pulumi.Input[str]]=None):
"\n The pod this Toleration is attached to tolerates any taint that matches the triple <key,value,effect> using the matching operator <operator>.\n :param pulumi.Input[str] effect: Effect indicates the taint effect to match. Empty means match all taint effects. When specified, allowed values are NoSchedule, PreferNoSchedule and NoExecute.\n :param pulumi.Input[str] key: Key is the taint key that the toleration applies to. Empty means match all taint keys. If the key is empty, operator must be Exists; this combination means to match all values and all keys.\n :param pulumi.Input[str] operator: Operator represents a key's relationship to the value. Valid operators are Exists and Equal. Defaults to Equal. Exists is equivalent to wildcard for value, so that a pod can tolerate all taints of a particular category.\n :param pulumi.Input[int] toleration_seconds: TolerationSeconds represents the period of time the toleration (which must be of effect NoExecute, otherwise this field is ignored) tolerates the taint. By default, it is not set, which means tolerate the taint forever (do not evict). Zero and negative values will be treated as 0 (evict immediately) by the system.\n :param pulumi.Input[str] value: Value is the taint value the toleration matches to. If the operator is Exists, the value should be empty, otherwise just a regular string.\n "
if (effect is not None):
pulumi.set(__self__, 'effect', effect)
if (key is not None):
pulumi.set(__self__, 'key', key)
if (operator is not None):
pulumi.set(__self__, 'operator', operator)
if (toleration_seconds is not None):
pulumi.set(__self__, 'toleration_seconds', toleration_seconds)
if (value is not None):
pulumi.set(__self__, 'value', value)
|
def __init__(__self__, *, effect: Optional[pulumi.Input[str]]=None, key: Optional[pulumi.Input[str]]=None, operator: Optional[pulumi.Input[str]]=None, toleration_seconds: Optional[pulumi.Input[int]]=None, value: Optional[pulumi.Input[str]]=None):
"\n The pod this Toleration is attached to tolerates any taint that matches the triple <key,value,effect> using the matching operator <operator>.\n :param pulumi.Input[str] effect: Effect indicates the taint effect to match. Empty means match all taint effects. When specified, allowed values are NoSchedule, PreferNoSchedule and NoExecute.\n :param pulumi.Input[str] key: Key is the taint key that the toleration applies to. Empty means match all taint keys. If the key is empty, operator must be Exists; this combination means to match all values and all keys.\n :param pulumi.Input[str] operator: Operator represents a key's relationship to the value. Valid operators are Exists and Equal. Defaults to Equal. Exists is equivalent to wildcard for value, so that a pod can tolerate all taints of a particular category.\n :param pulumi.Input[int] toleration_seconds: TolerationSeconds represents the period of time the toleration (which must be of effect NoExecute, otherwise this field is ignored) tolerates the taint. By default, it is not set, which means tolerate the taint forever (do not evict). Zero and negative values will be treated as 0 (evict immediately) by the system.\n :param pulumi.Input[str] value: Value is the taint value the toleration matches to. If the operator is Exists, the value should be empty, otherwise just a regular string.\n "
if (effect is not None):
pulumi.set(__self__, 'effect', effect)
if (key is not None):
pulumi.set(__self__, 'key', key)
if (operator is not None):
pulumi.set(__self__, 'operator', operator)
if (toleration_seconds is not None):
pulumi.set(__self__, 'toleration_seconds', toleration_seconds)
if (value is not None):
pulumi.set(__self__, 'value', value)<|docstring|>The pod this Toleration is attached to tolerates any taint that matches the triple <key,value,effect> using the matching operator <operator>.
:param pulumi.Input[str] effect: Effect indicates the taint effect to match. Empty means match all taint effects. When specified, allowed values are NoSchedule, PreferNoSchedule and NoExecute.
:param pulumi.Input[str] key: Key is the taint key that the toleration applies to. Empty means match all taint keys. If the key is empty, operator must be Exists; this combination means to match all values and all keys.
:param pulumi.Input[str] operator: Operator represents a key's relationship to the value. Valid operators are Exists and Equal. Defaults to Equal. Exists is equivalent to wildcard for value, so that a pod can tolerate all taints of a particular category.
:param pulumi.Input[int] toleration_seconds: TolerationSeconds represents the period of time the toleration (which must be of effect NoExecute, otherwise this field is ignored) tolerates the taint. By default, it is not set, which means tolerate the taint forever (do not evict). Zero and negative values will be treated as 0 (evict immediately) by the system.
:param pulumi.Input[str] value: Value is the taint value the toleration matches to. If the operator is Exists, the value should be empty, otherwise just a regular string.<|endoftext|>
|
96948b7e3758758871da06382ec6963c7b7bad0427c696a8cbf58506fa7334ab
|
@property
@pulumi.getter
def effect(self) -> Optional[pulumi.Input[str]]:
'\n Effect indicates the taint effect to match. Empty means match all taint effects. When specified, allowed values are NoSchedule, PreferNoSchedule and NoExecute.\n '
return pulumi.get(self, 'effect')
|
Effect indicates the taint effect to match. Empty means match all taint effects. When specified, allowed values are NoSchedule, PreferNoSchedule and NoExecute.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
effect
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter
def effect(self) -> Optional[pulumi.Input[str]]:
'\n \n '
return pulumi.get(self, 'effect')
|
@property
@pulumi.getter
def effect(self) -> Optional[pulumi.Input[str]]:
'\n \n '
return pulumi.get(self, 'effect')<|docstring|>Effect indicates the taint effect to match. Empty means match all taint effects. When specified, allowed values are NoSchedule, PreferNoSchedule and NoExecute.<|endoftext|>
|
56a17d7ed8f5e92d7706a8ffd2c55cb6cc3a6609d8cce8250c66fcf5c3ab27bb
|
@property
@pulumi.getter
def key(self) -> Optional[pulumi.Input[str]]:
'\n Key is the taint key that the toleration applies to. Empty means match all taint keys. If the key is empty, operator must be Exists; this combination means to match all values and all keys.\n '
return pulumi.get(self, 'key')
|
Key is the taint key that the toleration applies to. Empty means match all taint keys. If the key is empty, operator must be Exists; this combination means to match all values and all keys.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
key
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter
def key(self) -> Optional[pulumi.Input[str]]:
'\n \n '
return pulumi.get(self, 'key')
|
@property
@pulumi.getter
def key(self) -> Optional[pulumi.Input[str]]:
'\n \n '
return pulumi.get(self, 'key')<|docstring|>Key is the taint key that the toleration applies to. Empty means match all taint keys. If the key is empty, operator must be Exists; this combination means to match all values and all keys.<|endoftext|>
|
3c398ae7390efb94fe34d30e32ac9bcbaf5751730356d5b920a042bfe235940f
|
@property
@pulumi.getter
def operator(self) -> Optional[pulumi.Input[str]]:
"\n Operator represents a key's relationship to the value. Valid operators are Exists and Equal. Defaults to Equal. Exists is equivalent to wildcard for value, so that a pod can tolerate all taints of a particular category.\n "
return pulumi.get(self, 'operator')
|
Operator represents a key's relationship to the value. Valid operators are Exists and Equal. Defaults to Equal. Exists is equivalent to wildcard for value, so that a pod can tolerate all taints of a particular category.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
operator
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter
def operator(self) -> Optional[pulumi.Input[str]]:
"\n \n "
return pulumi.get(self, 'operator')
|
@property
@pulumi.getter
def operator(self) -> Optional[pulumi.Input[str]]:
"\n \n "
return pulumi.get(self, 'operator')<|docstring|>Operator represents a key's relationship to the value. Valid operators are Exists and Equal. Defaults to Equal. Exists is equivalent to wildcard for value, so that a pod can tolerate all taints of a particular category.<|endoftext|>
|
6904f5505ae78f512faf3af88f5928c30059929ce52f340f02f9ded6c50e1848
|
@property
@pulumi.getter(name='tolerationSeconds')
def toleration_seconds(self) -> Optional[pulumi.Input[int]]:
'\n TolerationSeconds represents the period of time the toleration (which must be of effect NoExecute, otherwise this field is ignored) tolerates the taint. By default, it is not set, which means tolerate the taint forever (do not evict). Zero and negative values will be treated as 0 (evict immediately) by the system.\n '
return pulumi.get(self, 'toleration_seconds')
|
TolerationSeconds represents the period of time the toleration (which must be of effect NoExecute, otherwise this field is ignored) tolerates the taint. By default, it is not set, which means tolerate the taint forever (do not evict). Zero and negative values will be treated as 0 (evict immediately) by the system.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
toleration_seconds
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter(name='tolerationSeconds')
def toleration_seconds(self) -> Optional[pulumi.Input[int]]:
'\n \n '
return pulumi.get(self, 'toleration_seconds')
|
@property
@pulumi.getter(name='tolerationSeconds')
def toleration_seconds(self) -> Optional[pulumi.Input[int]]:
'\n \n '
return pulumi.get(self, 'toleration_seconds')<|docstring|>TolerationSeconds represents the period of time the toleration (which must be of effect NoExecute, otherwise this field is ignored) tolerates the taint. By default, it is not set, which means tolerate the taint forever (do not evict). Zero and negative values will be treated as 0 (evict immediately) by the system.<|endoftext|>
|
b0fe514b57d90ee8e06cda410198addb22eb038e54215645c2c74e93b62fc20e
|
@property
@pulumi.getter
def value(self) -> Optional[pulumi.Input[str]]:
'\n Value is the taint value the toleration matches to. If the operator is Exists, the value should be empty, otherwise just a regular string.\n '
return pulumi.get(self, 'value')
|
Value is the taint value the toleration matches to. If the operator is Exists, the value should be empty, otherwise just a regular string.
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
value
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter
def value(self) -> Optional[pulumi.Input[str]]:
'\n \n '
return pulumi.get(self, 'value')
|
@property
@pulumi.getter
def value(self) -> Optional[pulumi.Input[str]]:
'\n \n '
return pulumi.get(self, 'value')<|docstring|>Value is the taint value the toleration matches to. If the operator is Exists, the value should be empty, otherwise just a regular string.<|endoftext|>
|
96c56414d6c976ea59bca3d4bdc116ca4bddbcfb02206dc949e0d31c8f32aa01
|
def __init__(__self__, *, name: pulumi.Input[str], repository: pulumi.Input[str], tag: pulumi.Input[str], image_pull_policy: Optional[pulumi.Input[str]]=None):
'\n :param pulumi.Input[str] name: The name of the csi sidecar image\n :param pulumi.Input[str] repository: The repository of the csi sidecar image\n :param pulumi.Input[str] tag: The tag of the csi sidecar image\n :param pulumi.Input[str] image_pull_policy: The pullPolicy of the csi sidecar image\n '
pulumi.set(__self__, 'name', name)
pulumi.set(__self__, 'repository', repository)
pulumi.set(__self__, 'tag', tag)
if (image_pull_policy is not None):
pulumi.set(__self__, 'image_pull_policy', image_pull_policy)
|
:param pulumi.Input[str] name: The name of the csi sidecar image
:param pulumi.Input[str] repository: The repository of the csi sidecar image
:param pulumi.Input[str] tag: The tag of the csi sidecar image
:param pulumi.Input[str] image_pull_policy: The pullPolicy of the csi sidecar image
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
__init__
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
def __init__(__self__, *, name: pulumi.Input[str], repository: pulumi.Input[str], tag: pulumi.Input[str], image_pull_policy: Optional[pulumi.Input[str]]=None):
'\n :param pulumi.Input[str] name: The name of the csi sidecar image\n :param pulumi.Input[str] repository: The repository of the csi sidecar image\n :param pulumi.Input[str] tag: The tag of the csi sidecar image\n :param pulumi.Input[str] image_pull_policy: The pullPolicy of the csi sidecar image\n '
pulumi.set(__self__, 'name', name)
pulumi.set(__self__, 'repository', repository)
pulumi.set(__self__, 'tag', tag)
if (image_pull_policy is not None):
pulumi.set(__self__, 'image_pull_policy', image_pull_policy)
|
def __init__(__self__, *, name: pulumi.Input[str], repository: pulumi.Input[str], tag: pulumi.Input[str], image_pull_policy: Optional[pulumi.Input[str]]=None):
'\n :param pulumi.Input[str] name: The name of the csi sidecar image\n :param pulumi.Input[str] repository: The repository of the csi sidecar image\n :param pulumi.Input[str] tag: The tag of the csi sidecar image\n :param pulumi.Input[str] image_pull_policy: The pullPolicy of the csi sidecar image\n '
pulumi.set(__self__, 'name', name)
pulumi.set(__self__, 'repository', repository)
pulumi.set(__self__, 'tag', tag)
if (image_pull_policy is not None):
pulumi.set(__self__, 'image_pull_policy', image_pull_policy)<|docstring|>:param pulumi.Input[str] name: The name of the csi sidecar image
:param pulumi.Input[str] repository: The repository of the csi sidecar image
:param pulumi.Input[str] tag: The tag of the csi sidecar image
:param pulumi.Input[str] image_pull_policy: The pullPolicy of the csi sidecar image<|endoftext|>
|
995aa8dc2ffc64a30940b58978b5187b273cfebd81ecb60c34ee30ad4e4b4640
|
@property
@pulumi.getter
def name(self) -> pulumi.Input[str]:
'\n The name of the csi sidecar image\n '
return pulumi.get(self, 'name')
|
The name of the csi sidecar image
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
name
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter
def name(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'name')
|
@property
@pulumi.getter
def name(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'name')<|docstring|>The name of the csi sidecar image<|endoftext|>
|
c4af764cc3c228af428be5db4e0ff708e605cf5918f11043c36ed7d09c2d6488
|
@property
@pulumi.getter
def repository(self) -> pulumi.Input[str]:
'\n The repository of the csi sidecar image\n '
return pulumi.get(self, 'repository')
|
The repository of the csi sidecar image
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
repository
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter
def repository(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'repository')
|
@property
@pulumi.getter
def repository(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'repository')<|docstring|>The repository of the csi sidecar image<|endoftext|>
|
62829ebcd6093edeb2d50b15c2fa9aeee4501bf9e627c8f119c8304d5798a303
|
@property
@pulumi.getter
def tag(self) -> pulumi.Input[str]:
'\n The tag of the csi sidecar image\n '
return pulumi.get(self, 'tag')
|
The tag of the csi sidecar image
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
tag
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter
def tag(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'tag')
|
@property
@pulumi.getter
def tag(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'tag')<|docstring|>The tag of the csi sidecar image<|endoftext|>
|
03d48c8084798eaf07d29f41a9b9263b29fd38f8c64a030a944bcb49e5803cb1
|
@property
@pulumi.getter(name='imagePullPolicy')
def image_pull_policy(self) -> Optional[pulumi.Input[str]]:
'\n The pullPolicy of the csi sidecar image\n '
return pulumi.get(self, 'image_pull_policy')
|
The pullPolicy of the csi sidecar image
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
image_pull_policy
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter(name='imagePullPolicy')
def image_pull_policy(self) -> Optional[pulumi.Input[str]]:
'\n \n '
return pulumi.get(self, 'image_pull_policy')
|
@property
@pulumi.getter(name='imagePullPolicy')
def image_pull_policy(self) -> Optional[pulumi.Input[str]]:
'\n \n '
return pulumi.get(self, 'image_pull_policy')<|docstring|>The pullPolicy of the csi sidecar image<|endoftext|>
|
ebde0a257f57d193268d6ca2f13646e84699b14640005b1554ce458e663c71b3
|
def __init__(__self__, *, controller_ready: pulumi.Input[bool], node_ready: pulumi.Input[bool], phase: pulumi.Input[str], version: pulumi.Input[str]):
'\n IBMBlockCSIStatus defines the observed state of IBMBlockCSI\n :param pulumi.Input[str] phase: Phase is the driver running phase\n :param pulumi.Input[str] version: Version is the current driver version\n '
pulumi.set(__self__, 'controller_ready', controller_ready)
pulumi.set(__self__, 'node_ready', node_ready)
pulumi.set(__self__, 'phase', phase)
pulumi.set(__self__, 'version', version)
|
IBMBlockCSIStatus defines the observed state of IBMBlockCSI
:param pulumi.Input[str] phase: Phase is the driver running phase
:param pulumi.Input[str] version: Version is the current driver version
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
__init__
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
def __init__(__self__, *, controller_ready: pulumi.Input[bool], node_ready: pulumi.Input[bool], phase: pulumi.Input[str], version: pulumi.Input[str]):
'\n IBMBlockCSIStatus defines the observed state of IBMBlockCSI\n :param pulumi.Input[str] phase: Phase is the driver running phase\n :param pulumi.Input[str] version: Version is the current driver version\n '
pulumi.set(__self__, 'controller_ready', controller_ready)
pulumi.set(__self__, 'node_ready', node_ready)
pulumi.set(__self__, 'phase', phase)
pulumi.set(__self__, 'version', version)
|
def __init__(__self__, *, controller_ready: pulumi.Input[bool], node_ready: pulumi.Input[bool], phase: pulumi.Input[str], version: pulumi.Input[str]):
'\n IBMBlockCSIStatus defines the observed state of IBMBlockCSI\n :param pulumi.Input[str] phase: Phase is the driver running phase\n :param pulumi.Input[str] version: Version is the current driver version\n '
pulumi.set(__self__, 'controller_ready', controller_ready)
pulumi.set(__self__, 'node_ready', node_ready)
pulumi.set(__self__, 'phase', phase)
pulumi.set(__self__, 'version', version)<|docstring|>IBMBlockCSIStatus defines the observed state of IBMBlockCSI
:param pulumi.Input[str] phase: Phase is the driver running phase
:param pulumi.Input[str] version: Version is the current driver version<|endoftext|>
|
bd6f8d168a899ef88b3140dabfd7cfecc372a97619ec53cd460c38fa36d489ef
|
@property
@pulumi.getter
def phase(self) -> pulumi.Input[str]:
'\n Phase is the driver running phase\n '
return pulumi.get(self, 'phase')
|
Phase is the driver running phase
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
phase
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter
def phase(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'phase')
|
@property
@pulumi.getter
def phase(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'phase')<|docstring|>Phase is the driver running phase<|endoftext|>
|
7aaf505a0e12d7644f2b2d45fbad3629656e3b21c903bd7f4157383f3418273f
|
@property
@pulumi.getter
def version(self) -> pulumi.Input[str]:
'\n Version is the current driver version\n '
return pulumi.get(self, 'version')
|
Version is the current driver version
|
operators/ibm-block-csi-operator-community/python/pulumi_pulumi_kubernetes_crds_operators_ibm_block_csi_operator_community/csi/v1/_inputs.py
|
version
|
pulumi/pulumi-kubernetes-crds
| 0 |
python
|
@property
@pulumi.getter
def version(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'version')
|
@property
@pulumi.getter
def version(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'version')<|docstring|>Version is the current driver version<|endoftext|>
|
4c51c550d851828b1f6ad62a53f25747bd7fa42f5e8c05d865aac67ce223c4c4
|
@django_view
@ajax_request
@admin_cm_permission
def cma_ajax_get_table_templates(request):
'\n Ajax view fetching template list.\n '
if (request.method == 'GET'):
templates = prep_data('admin_cm/template/get_list/', request.session)
for item in templates:
item['ec2name'] = ec2names_reversed[item['ec2name']]
item['memory'] = filesizeformatmb(item['memory'])
return messages_ajax.success(templates)
|
Ajax view fetching template list.
|
src/wi/views/admin_cm/template.py
|
cma_ajax_get_table_templates
|
cc1-cloud/cc1
| 11 |
python
|
@django_view
@ajax_request
@admin_cm_permission
def cma_ajax_get_table_templates(request):
'\n \n '
if (request.method == 'GET'):
templates = prep_data('admin_cm/template/get_list/', request.session)
for item in templates:
item['ec2name'] = ec2names_reversed[item['ec2name']]
item['memory'] = filesizeformatmb(item['memory'])
return messages_ajax.success(templates)
|
@django_view
@ajax_request
@admin_cm_permission
def cma_ajax_get_table_templates(request):
'\n \n '
if (request.method == 'GET'):
templates = prep_data('admin_cm/template/get_list/', request.session)
for item in templates:
item['ec2name'] = ec2names_reversed[item['ec2name']]
item['memory'] = filesizeformatmb(item['memory'])
return messages_ajax.success(templates)<|docstring|>Ajax view fetching template list.<|endoftext|>
|
a650b746d44b5c6e2cf26fac0c71cc1c819ad8e3862cf530456a268303661d25
|
@property
def name(self):
'\n Returns a room name.\n\n :return: A room name.\n :rtype: str\n '
return self._data.get('room', '')
|
Returns a room name.
:return: A room name.
:rtype: str
|
lc.py
|
name
|
liquidthex/nortbot
| 0 |
python
|
@property
def name(self):
'\n Returns a room name.\n\n :return: A room name.\n :rtype: str\n '
return self._data.get('room', )
|
@property
def name(self):
'\n Returns a room name.\n\n :return: A room name.\n :rtype: str\n '
return self._data.get('room', )<|docstring|>Returns a room name.
:return: A room name.
:rtype: str<|endoftext|>
|
14586989cbfdeb9117dc7af23357997fb17b3cff23b27183a6cc20c223df3ce4
|
@property
def users(self):
"\n Returns room users.\n\n :return: Room users'\n :rtype: int\n "
return self._data.get('users', 0)
|
Returns room users.
:return: Room users'
:rtype: int
|
lc.py
|
users
|
liquidthex/nortbot
| 0 |
python
|
@property
def users(self):
"\n Returns room users.\n\n :return: Room users'\n :rtype: int\n "
return self._data.get('users', 0)
|
@property
def users(self):
"\n Returns room users.\n\n :return: Room users'\n :rtype: int\n "
return self._data.get('users', 0)<|docstring|>Returns room users.
:return: Room users'
:rtype: int<|endoftext|>
|
8094a52ce90846add78f66639fa69ad76f64dca185ea1b7e6ec926056fa1065a
|
@property
def broadcasters(self):
'\n Returns room broadcasters.\n\n :return: Room broadcasters.\n :rtype: int\n '
return self._data.get('broadcasters', 0)
|
Returns room broadcasters.
:return: Room broadcasters.
:rtype: int
|
lc.py
|
broadcasters
|
liquidthex/nortbot
| 0 |
python
|
@property
def broadcasters(self):
'\n Returns room broadcasters.\n\n :return: Room broadcasters.\n :rtype: int\n '
return self._data.get('broadcasters', 0)
|
@property
def broadcasters(self):
'\n Returns room broadcasters.\n\n :return: Room broadcasters.\n :rtype: int\n '
return self._data.get('broadcasters', 0)<|docstring|>Returns room broadcasters.
:return: Room broadcasters.
:rtype: int<|endoftext|>
|
963494d18f88933e3f9d9e384db78bfccdb855d7eb7d92bd4999bd73afa4625e
|
def __init__(self, bot, watch=None):
'\n Initialize the LiveCount class.\n\n :param bot: A instance of NortBot.\n :param watch: A room name to watch.\n :type watch: str | None\n '
self._bot = bot
self._watch_rooms = [watch]
self._watch_interval = 20
self._last_update_time = 0
self._most_active = Room()
self._connected = False
self._ws = None
|
Initialize the LiveCount class.
:param bot: A instance of NortBot.
:param watch: A room name to watch.
:type watch: str | None
|
lc.py
|
__init__
|
liquidthex/nortbot
| 0 |
python
|
def __init__(self, bot, watch=None):
'\n Initialize the LiveCount class.\n\n :param bot: A instance of NortBot.\n :param watch: A room name to watch.\n :type watch: str | None\n '
self._bot = bot
self._watch_rooms = [watch]
self._watch_interval = 20
self._last_update_time = 0
self._most_active = Room()
self._connected = False
self._ws = None
|
def __init__(self, bot, watch=None):
'\n Initialize the LiveCount class.\n\n :param bot: A instance of NortBot.\n :param watch: A room name to watch.\n :type watch: str | None\n '
self._bot = bot
self._watch_rooms = [watch]
self._watch_interval = 20
self._last_update_time = 0
self._most_active = Room()
self._connected = False
self._ws = None<|docstring|>Initialize the LiveCount class.
:param bot: A instance of NortBot.
:param watch: A room name to watch.
:type watch: str | None<|endoftext|>
|
860ed382194f1cc220d3491fabebd6cb56f7223ef9386d820ab15ca6b0b3f2a2
|
@property
def connected(self):
'\n Returns a bool based on the connection state.\n\n :return: True if connected.\n :rtype: bool\n '
return self._connected
|
Returns a bool based on the connection state.
:return: True if connected.
:rtype: bool
|
lc.py
|
connected
|
liquidthex/nortbot
| 0 |
python
|
@property
def connected(self):
'\n Returns a bool based on the connection state.\n\n :return: True if connected.\n :rtype: bool\n '
return self._connected
|
@property
def connected(self):
'\n Returns a bool based on the connection state.\n\n :return: True if connected.\n :rtype: bool\n '
return self._connected<|docstring|>Returns a bool based on the connection state.
:return: True if connected.
:rtype: bool<|endoftext|>
|
a7d7df66d4ce3328c533e72f8d82ee1b32e6613a9c648f365a728ce94f71fa62
|
def most_active(self):
'\n Returns the most active room.\n\n :return: The room with the most users.\n :rtype: Room\n '
if self.connected:
ma = ('Most active: %s, Users: %s, Broadcasters: %s' % (self._most_active.name, self._most_active.users, self._most_active.broadcasters))
self._bot.responder(ma)
|
Returns the most active room.
:return: The room with the most users.
:rtype: Room
|
lc.py
|
most_active
|
liquidthex/nortbot
| 0 |
python
|
def most_active(self):
'\n Returns the most active room.\n\n :return: The room with the most users.\n :rtype: Room\n '
if self.connected:
ma = ('Most active: %s, Users: %s, Broadcasters: %s' % (self._most_active.name, self._most_active.users, self._most_active.broadcasters))
self._bot.responder(ma)
|
def most_active(self):
'\n Returns the most active room.\n\n :return: The room with the most users.\n :rtype: Room\n '
if self.connected:
ma = ('Most active: %s, Users: %s, Broadcasters: %s' % (self._most_active.name, self._most_active.users, self._most_active.broadcasters))
self._bot.responder(ma)<|docstring|>Returns the most active room.
:return: The room with the most users.
:rtype: Room<|endoftext|>
|
6d7006e74447cc2b7bb133753035b57774d6fe58eb67509ec349ac507a3260b9
|
def status(self):
'\n Show live count status.\n '
if self.connected:
stats = [('Live connected: %s' % self.connected), ('Live count watch room %s' % len(self._watch_rooms)), ('Live count interval: %s' % self._watch_interval), ('Most active room: %s' % self.most_active)]
self._bot.responder('\n'.join(stats))
|
Show live count status.
|
lc.py
|
status
|
liquidthex/nortbot
| 0 |
python
|
def status(self):
'\n \n '
if self.connected:
stats = [('Live connected: %s' % self.connected), ('Live count watch room %s' % len(self._watch_rooms)), ('Live count interval: %s' % self._watch_interval), ('Most active room: %s' % self.most_active)]
self._bot.responder('\n'.join(stats))
|
def status(self):
'\n \n '
if self.connected:
stats = [('Live connected: %s' % self.connected), ('Live count watch room %s' % len(self._watch_rooms)), ('Live count interval: %s' % self._watch_interval), ('Most active room: %s' % self.most_active)]
self._bot.responder('\n'.join(stats))<|docstring|>Show live count status.<|endoftext|>
|
e6d33924dd3823bb2c540a62b4b0b307d7b7abefcada03e1b6db58adc2062169
|
def add_watch_room(self, room_name):
'\n Set a room name to watch live count for.\n\n :param room_name: The room name to watch.\n :type room_name: str\n '
if self.connected:
self._watch_rooms.append(room_name)
self._bot.responder(('Added %s to live watch.' % room_name))
|
Set a room name to watch live count for.
:param room_name: The room name to watch.
:type room_name: str
|
lc.py
|
add_watch_room
|
liquidthex/nortbot
| 0 |
python
|
def add_watch_room(self, room_name):
'\n Set a room name to watch live count for.\n\n :param room_name: The room name to watch.\n :type room_name: str\n '
if self.connected:
self._watch_rooms.append(room_name)
self._bot.responder(('Added %s to live watch.' % room_name))
|
def add_watch_room(self, room_name):
'\n Set a room name to watch live count for.\n\n :param room_name: The room name to watch.\n :type room_name: str\n '
if self.connected:
self._watch_rooms.append(room_name)
self._bot.responder(('Added %s to live watch.' % room_name))<|docstring|>Set a room name to watch live count for.
:param room_name: The room name to watch.
:type room_name: str<|endoftext|>
|
40eee59fa589897fd440822a12350512b7346aae6005800625da21dc5e7c054a
|
def remove_watch_room(self, room_name):
'\n Remove a room name from the live count watch rooms.\n\n :param room_name: The room name to remove.\n :type room_name: str\n '
if self.connected:
if (room_name in self._watch_rooms):
self._watch_rooms.remove(room_name)
self._bot.responder(('Removed %s from watch rooms.' % room_name))
else:
self._bot.responder(('%s is not in the watch rooms.' % room_name))
|
Remove a room name from the live count watch rooms.
:param room_name: The room name to remove.
:type room_name: str
|
lc.py
|
remove_watch_room
|
liquidthex/nortbot
| 0 |
python
|
def remove_watch_room(self, room_name):
'\n Remove a room name from the live count watch rooms.\n\n :param room_name: The room name to remove.\n :type room_name: str\n '
if self.connected:
if (room_name in self._watch_rooms):
self._watch_rooms.remove(room_name)
self._bot.responder(('Removed %s from watch rooms.' % room_name))
else:
self._bot.responder(('%s is not in the watch rooms.' % room_name))
|
def remove_watch_room(self, room_name):
'\n Remove a room name from the live count watch rooms.\n\n :param room_name: The room name to remove.\n :type room_name: str\n '
if self.connected:
if (room_name in self._watch_rooms):
self._watch_rooms.remove(room_name)
self._bot.responder(('Removed %s from watch rooms.' % room_name))
else:
self._bot.responder(('%s is not in the watch rooms.' % room_name))<|docstring|>Remove a room name from the live count watch rooms.
:param room_name: The room name to remove.
:type room_name: str<|endoftext|>
|
9ad4744b7ac18ebd6be28c579c12e83d0b6492709f41d26f8399dd63e0dccad1
|
def set_watch_interval(self, interval):
'\n Set the watch interval time.\n\n :param interval: Watch interval time in seconds.\n :type interval: int\n '
if self.connected:
self._watch_interval = interval
self._bot.responder(('Live count watch interval: %s' % interval))
|
Set the watch interval time.
:param interval: Watch interval time in seconds.
:type interval: int
|
lc.py
|
set_watch_interval
|
liquidthex/nortbot
| 0 |
python
|
def set_watch_interval(self, interval):
'\n Set the watch interval time.\n\n :param interval: Watch interval time in seconds.\n :type interval: int\n '
if self.connected:
self._watch_interval = interval
self._bot.responder(('Live count watch interval: %s' % interval))
|
def set_watch_interval(self, interval):
'\n Set the watch interval time.\n\n :param interval: Watch interval time in seconds.\n :type interval: int\n '
if self.connected:
self._watch_interval = interval
self._bot.responder(('Live count watch interval: %s' % interval))<|docstring|>Set the watch interval time.
:param interval: Watch interval time in seconds.
:type interval: int<|endoftext|>
|
0c20fa35c561d87e3a4c8e09a4386ddbb130cb2e8d12c73443cd711520af8a5e
|
def connect(self):
'\n Connect to the websocket endpoint.\n '
tc_header = {'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; WOW64; rv:66.0) Gecko/20100101 Firefox/66.0', 'Accept-Language': 'en-US,en;q=0.5', 'Accept-Encoding': 'gzip, deflate, br', 'Sec-WebSocket-Extensions': 'permessage-deflate'}
self._ws = websocket.create_connection('wss://lb-stat.tinychat.com/leaderboard', header=tc_header, origin='https://tinychat.com')
if self._ws.connected:
self._bot.responder('Live count connected.')
self._connected = self._ws.connected
self._listener()
else:
log.debug('connection to live counter failed')
|
Connect to the websocket endpoint.
|
lc.py
|
connect
|
liquidthex/nortbot
| 0 |
python
|
def connect(self):
'\n \n '
tc_header = {'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; WOW64; rv:66.0) Gecko/20100101 Firefox/66.0', 'Accept-Language': 'en-US,en;q=0.5', 'Accept-Encoding': 'gzip, deflate, br', 'Sec-WebSocket-Extensions': 'permessage-deflate'}
self._ws = websocket.create_connection('wss://lb-stat.tinychat.com/leaderboard', header=tc_header, origin='https://tinychat.com')
if self._ws.connected:
self._bot.responder('Live count connected.')
self._connected = self._ws.connected
self._listener()
else:
log.debug('connection to live counter failed')
|
def connect(self):
'\n \n '
tc_header = {'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; WOW64; rv:66.0) Gecko/20100101 Firefox/66.0', 'Accept-Language': 'en-US,en;q=0.5', 'Accept-Encoding': 'gzip, deflate, br', 'Sec-WebSocket-Extensions': 'permessage-deflate'}
self._ws = websocket.create_connection('wss://lb-stat.tinychat.com/leaderboard', header=tc_header, origin='https://tinychat.com')
if self._ws.connected:
self._bot.responder('Live count connected.')
self._connected = self._ws.connected
self._listener()
else:
log.debug('connection to live counter failed')<|docstring|>Connect to the websocket endpoint.<|endoftext|>
|
34617c37321f948071c10e828e3cf82b08a4d16e0ccc16712e500249efea139a
|
def disconnect(self):
'\n Disconnect from the websocket.\n '
self._bot.responder('Closing live count.')
self._connected = False
self._ws = None
self._watch_rooms = []
|
Disconnect from the websocket.
|
lc.py
|
disconnect
|
liquidthex/nortbot
| 0 |
python
|
def disconnect(self):
'\n \n '
self._bot.responder('Closing live count.')
self._connected = False
self._ws = None
self._watch_rooms = []
|
def disconnect(self):
'\n \n '
self._bot.responder('Closing live count.')
self._connected = False
self._ws = None
self._watch_rooms = []<|docstring|>Disconnect from the websocket.<|endoftext|>
|
b3960f4ad295092b72415d9a45f5d1198ff57d4e35d8c18b44468237ca241d15
|
def on_update(self, data):
'\n Received when ever the live count gets updated.\n\n :param data: A list containing room updates.\n :type data: list\n '
log.debug(('live count items %s' % len(data)))
ts = time.time()
rooms = []
for room_data in data:
room = Room(**room_data)
if (room.users > self._most_active.users):
self._most_active = room
if (len(self._watch_rooms) > 0):
if (room.name in self._watch_rooms):
info = ('Watching: %s, Users: %s, Broadcasters: %s' % (room.name, room.users, room.broadcasters))
rooms.append(info)
if (len(rooms) > 0):
if ((ts - self._last_update_time) >= self._watch_interval):
self._last_update_time = ts
self._bot.responder('\n'.join(rooms))
|
Received when ever the live count gets updated.
:param data: A list containing room updates.
:type data: list
|
lc.py
|
on_update
|
liquidthex/nortbot
| 0 |
python
|
def on_update(self, data):
'\n Received when ever the live count gets updated.\n\n :param data: A list containing room updates.\n :type data: list\n '
log.debug(('live count items %s' % len(data)))
ts = time.time()
rooms = []
for room_data in data:
room = Room(**room_data)
if (room.users > self._most_active.users):
self._most_active = room
if (len(self._watch_rooms) > 0):
if (room.name in self._watch_rooms):
info = ('Watching: %s, Users: %s, Broadcasters: %s' % (room.name, room.users, room.broadcasters))
rooms.append(info)
if (len(rooms) > 0):
if ((ts - self._last_update_time) >= self._watch_interval):
self._last_update_time = ts
self._bot.responder('\n'.join(rooms))
|
def on_update(self, data):
'\n Received when ever the live count gets updated.\n\n :param data: A list containing room updates.\n :type data: list\n '
log.debug(('live count items %s' % len(data)))
ts = time.time()
rooms = []
for room_data in data:
room = Room(**room_data)
if (room.users > self._most_active.users):
self._most_active = room
if (len(self._watch_rooms) > 0):
if (room.name in self._watch_rooms):
info = ('Watching: %s, Users: %s, Broadcasters: %s' % (room.name, room.users, room.broadcasters))
rooms.append(info)
if (len(rooms) > 0):
if ((ts - self._last_update_time) >= self._watch_interval):
self._last_update_time = ts
self._bot.responder('\n'.join(rooms))<|docstring|>Received when ever the live count gets updated.
:param data: A list containing room updates.
:type data: list<|endoftext|>
|
d5d4fa3d9468d9aaec61eafdba7d1590b84e3cca56b2f527168f23e76dd93565
|
def getch(timeout=0.01):
'\n Retrieves a character from stdin.\n\n Returns None if no character is available within the timeout.\n Blocks if timeout < 0.\n '
if (not sys.stdin.isatty()):
return sys.stdin.read(1)
fileno = sys.stdin.fileno()
old_settings = termios.tcgetattr(fileno)
ch = None
try:
tty.setraw(fileno)
rlist = [fileno]
if (timeout >= 0):
[rlist, _, _] = select(rlist, [], [], timeout)
if (fileno in rlist):
ch = sys.stdin.read(1)
except Exception as ex:
print('getch', ex)
raise OSError
finally:
termios.tcsetattr(fileno, termios.TCSADRAIN, old_settings)
return ch
|
Retrieves a character from stdin.
Returns None if no character is available within the timeout.
Blocks if timeout < 0.
|
franka_interface/src/franka_dataflow/getch.py
|
getch
|
minoring/franka_ros_interface
| 91 |
python
|
def getch(timeout=0.01):
'\n Retrieves a character from stdin.\n\n Returns None if no character is available within the timeout.\n Blocks if timeout < 0.\n '
if (not sys.stdin.isatty()):
return sys.stdin.read(1)
fileno = sys.stdin.fileno()
old_settings = termios.tcgetattr(fileno)
ch = None
try:
tty.setraw(fileno)
rlist = [fileno]
if (timeout >= 0):
[rlist, _, _] = select(rlist, [], [], timeout)
if (fileno in rlist):
ch = sys.stdin.read(1)
except Exception as ex:
print('getch', ex)
raise OSError
finally:
termios.tcsetattr(fileno, termios.TCSADRAIN, old_settings)
return ch
|
def getch(timeout=0.01):
'\n Retrieves a character from stdin.\n\n Returns None if no character is available within the timeout.\n Blocks if timeout < 0.\n '
if (not sys.stdin.isatty()):
return sys.stdin.read(1)
fileno = sys.stdin.fileno()
old_settings = termios.tcgetattr(fileno)
ch = None
try:
tty.setraw(fileno)
rlist = [fileno]
if (timeout >= 0):
[rlist, _, _] = select(rlist, [], [], timeout)
if (fileno in rlist):
ch = sys.stdin.read(1)
except Exception as ex:
print('getch', ex)
raise OSError
finally:
termios.tcsetattr(fileno, termios.TCSADRAIN, old_settings)
return ch<|docstring|>Retrieves a character from stdin.
Returns None if no character is available within the timeout.
Blocks if timeout < 0.<|endoftext|>
|
66b3ebbb296b2b132b1c8f3e7385051413bc3efb82b90da10a908733a9dbd700
|
def transform(self, X, y=None):
'Transforms data X.\n\n Arguments:\n X (ww.DataTable, pd.DataFrame): Data to transform.\n y (ww.DataColumn, pd.Series, optional): Target data.\n\n Returns:\n ww.DataTable: Transformed X\n '
X_ww = infer_feature_types(X)
X = _convert_woodwork_types_wrapper(X_ww.to_dataframe())
if (y is not None):
y = infer_feature_types(y)
y = _convert_woodwork_types_wrapper(y.to_series())
try:
X_t = self._component_obj.transform(X, y)
except AttributeError:
raise MethodPropertyNotFoundError('Transformer requires a transform method or a component_obj that implements transform')
X_t_df = pd.DataFrame(X_t, columns=X.columns, index=X.index)
return _retain_custom_types_and_initalize_woodwork(X_ww, X_t_df)
|
Transforms data X.
Arguments:
X (ww.DataTable, pd.DataFrame): Data to transform.
y (ww.DataColumn, pd.Series, optional): Target data.
Returns:
ww.DataTable: Transformed X
|
evalml/pipelines/components/transformers/transformer.py
|
transform
|
skvorekn/evalml
| 0 |
python
|
def transform(self, X, y=None):
'Transforms data X.\n\n Arguments:\n X (ww.DataTable, pd.DataFrame): Data to transform.\n y (ww.DataColumn, pd.Series, optional): Target data.\n\n Returns:\n ww.DataTable: Transformed X\n '
X_ww = infer_feature_types(X)
X = _convert_woodwork_types_wrapper(X_ww.to_dataframe())
if (y is not None):
y = infer_feature_types(y)
y = _convert_woodwork_types_wrapper(y.to_series())
try:
X_t = self._component_obj.transform(X, y)
except AttributeError:
raise MethodPropertyNotFoundError('Transformer requires a transform method or a component_obj that implements transform')
X_t_df = pd.DataFrame(X_t, columns=X.columns, index=X.index)
return _retain_custom_types_and_initalize_woodwork(X_ww, X_t_df)
|
def transform(self, X, y=None):
'Transforms data X.\n\n Arguments:\n X (ww.DataTable, pd.DataFrame): Data to transform.\n y (ww.DataColumn, pd.Series, optional): Target data.\n\n Returns:\n ww.DataTable: Transformed X\n '
X_ww = infer_feature_types(X)
X = _convert_woodwork_types_wrapper(X_ww.to_dataframe())
if (y is not None):
y = infer_feature_types(y)
y = _convert_woodwork_types_wrapper(y.to_series())
try:
X_t = self._component_obj.transform(X, y)
except AttributeError:
raise MethodPropertyNotFoundError('Transformer requires a transform method or a component_obj that implements transform')
X_t_df = pd.DataFrame(X_t, columns=X.columns, index=X.index)
return _retain_custom_types_and_initalize_woodwork(X_ww, X_t_df)<|docstring|>Transforms data X.
Arguments:
X (ww.DataTable, pd.DataFrame): Data to transform.
y (ww.DataColumn, pd.Series, optional): Target data.
Returns:
ww.DataTable: Transformed X<|endoftext|>
|
9b25c23229d816e8bad0c017f90268fcb78a491222347e34ccaca7f807cef230
|
def fit_transform(self, X, y=None):
'Fits on X and transforms X\n\n Arguments:\n X (ww.DataTable, pd.DataFrame): Data to fit and transform\n y (ww.DataColumn, pd.Series): Target data\n\n Returns:\n ww.DataTable: Transformed X\n '
X_ww = infer_feature_types(X)
X_pd = _convert_woodwork_types_wrapper(X_ww.to_dataframe())
if (y is not None):
y_ww = infer_feature_types(y)
y_pd = _convert_woodwork_types_wrapper(y_ww.to_series())
try:
X_t = self._component_obj.fit_transform(X_pd, y_pd)
return _retain_custom_types_and_initalize_woodwork(X_ww, X_t)
except AttributeError:
try:
return self.fit(X, y).transform(X, y)
except MethodPropertyNotFoundError as e:
raise e
|
Fits on X and transforms X
Arguments:
X (ww.DataTable, pd.DataFrame): Data to fit and transform
y (ww.DataColumn, pd.Series): Target data
Returns:
ww.DataTable: Transformed X
|
evalml/pipelines/components/transformers/transformer.py
|
fit_transform
|
skvorekn/evalml
| 0 |
python
|
def fit_transform(self, X, y=None):
'Fits on X and transforms X\n\n Arguments:\n X (ww.DataTable, pd.DataFrame): Data to fit and transform\n y (ww.DataColumn, pd.Series): Target data\n\n Returns:\n ww.DataTable: Transformed X\n '
X_ww = infer_feature_types(X)
X_pd = _convert_woodwork_types_wrapper(X_ww.to_dataframe())
if (y is not None):
y_ww = infer_feature_types(y)
y_pd = _convert_woodwork_types_wrapper(y_ww.to_series())
try:
X_t = self._component_obj.fit_transform(X_pd, y_pd)
return _retain_custom_types_and_initalize_woodwork(X_ww, X_t)
except AttributeError:
try:
return self.fit(X, y).transform(X, y)
except MethodPropertyNotFoundError as e:
raise e
|
def fit_transform(self, X, y=None):
'Fits on X and transforms X\n\n Arguments:\n X (ww.DataTable, pd.DataFrame): Data to fit and transform\n y (ww.DataColumn, pd.Series): Target data\n\n Returns:\n ww.DataTable: Transformed X\n '
X_ww = infer_feature_types(X)
X_pd = _convert_woodwork_types_wrapper(X_ww.to_dataframe())
if (y is not None):
y_ww = infer_feature_types(y)
y_pd = _convert_woodwork_types_wrapper(y_ww.to_series())
try:
X_t = self._component_obj.fit_transform(X_pd, y_pd)
return _retain_custom_types_and_initalize_woodwork(X_ww, X_t)
except AttributeError:
try:
return self.fit(X, y).transform(X, y)
except MethodPropertyNotFoundError as e:
raise e<|docstring|>Fits on X and transforms X
Arguments:
X (ww.DataTable, pd.DataFrame): Data to fit and transform
y (ww.DataColumn, pd.Series): Target data
Returns:
ww.DataTable: Transformed X<|endoftext|>
|
96e2c89ad03983038f05fd05f677bc56605d4006173b62757a5f4b53153fbee9
|
def make_functions_chart(parser, metric='efpkg'):
'Writes XML file for functions chart and generates Krona plot from it\n\n Args:\n parser (:obj:DiamondParser): parser object with annotated reads\n metric (str): scoring metric (efpkg by default)\n '
outfile = os.path.join(parser.options.get_project_dir(parser.sample.sample_id), parser.options.get_output_subdir(parser.sample.sample_id), ((((parser.sample.sample_id + '_') + parser.end) + '_') + parser.options.xml_name))
with open(outfile, 'w') as out:
if (metric == 'proteincount'):
metric = 'readcount'
out.write((((((('<krona key="false">\n' + '\t<attributes magnitude="') + metric) + '">\n') + '\t\t<attribute display="Protein count">') + metric) + '</attribute>\n'))
else:
out.write((((('<krona key="false">\n' + '\t<attributes magnitude="') + metric) + '">\n') + '\t\t<attribute display="Read count">readcount</attribute>\n'))
if (metric != 'readcount'):
out.write((((('\t\t<attribute display="Score:' + metric) + '">') + metric) + '</attribute>\n'))
out.write(((((('\t\t<attribute display="AAI %" mono="true">identity</attribute>\n' + '\t</attributes>\n') + ' '.join(['\t<color attribute="identity"', 'valueStart="50"', 'valueEnd="100"', 'hueStart="0"', 'hueEnd="240"', 'default="true"></color>\n'])) + '\t<datasets>\n\t\t<dataset>') + parser.sample.sample_id) + '</dataset>\n\t</datasets>\n'))
read_count = 0
total_rpkm = 0.0
groups_rpkm = defaultdict(float)
groups_counts = defaultdict(set)
groups_identity = defaultdict(list)
functions_counts = defaultdict(set)
functions_rpkm = defaultdict(float)
functions_identity = defaultdict(list)
for (_, read) in parser.reads.items():
if (read.status == STATUS_GOOD):
read_count += 1
for function in read.functions:
total_rpkm += read.functions[function]
groups_counts[parser.ref_data.lookup_function_group(function)].add(read.read_id)
functions_rpkm[function] += read.functions[function]
groups_rpkm[parser.ref_data.lookup_function_group(function)] += read.functions[function]
functions_counts[function].add(read.read_id)
for hit in read.hit_list.hits:
for function in hit.functions:
functions_identity[function].append(hit.identity)
groups_identity[parser.ref_data.lookup_function_group(function)].append(hit.identity)
out.write((((('\t<node name="' + parser.sample.sample_id) + '_') + parser.end) + '">\n'))
if (metric != 'readcount'):
out.write((('\t\t<readcount><val>' + str(read_count)) + '</val></readcount>\n'))
out.write((((((('\t\t<' + metric) + '><val>') + str(total_rpkm)) + '</val></') + metric) + '>\n'))
for group in groups_rpkm:
out.write((('\t\t<node name="' + group) + '">\n'))
if (metric != 'readcount'):
out.write((('\t\t\t<readcount><val>' + str(len(groups_counts[group]))) + '</val></readcount>\n'))
out.write((((((('\t\t\t<' + metric) + '><val>') + str(groups_rpkm[group])) + '</val></') + metric) + '>\n'))
if (group in groups_identity):
out.write((('\t\t\t<identity><val>' + str((sum(groups_identity[group]) / len(groups_identity[group])))) + '</val></identity>\n'))
else:
out.write('\t\t\t<identity><val>0.0</val></identity>\n')
for function in parser.ref_data.get_functions_in_group(group):
if (function in functions_rpkm):
out.write((('\t\t\t<node name="' + function) + '">\n'))
if (metric != 'readcount'):
out.write((('\t\t\t\t<readcount><val>' + str(len(functions_counts[function]))) + '</val></readcount>\n'))
out.write((((((('\t\t\t\t<' + metric) + '><val>') + str(functions_rpkm[function])) + '</val></') + metric) + '>\n'))
if (function in functions_identity):
out.write((('\t\t\t\t<identity><val>' + str((sum(functions_identity[function]) / len(functions_identity[function])))) + '</val></identity>\n'))
else:
out.write('\t\t\t\t<identity><val>0.0</val></identity>\n')
out.write('\t\t\t</node>\n')
out.write('\t\t</node>\n')
out.write('\t</node>\n</krona>')
html_file = os.path.join(parser.options.get_project_dir(parser.sample.sample_id), parser.options.get_output_subdir(parser.sample.sample_id), ((((parser.sample.sample_id + '_') + parser.end) + '_') + parser.options.html_name))
run_external_program([parser.config.krona_path, '-o', html_file, outfile])
|
Writes XML file for functions chart and generates Krona plot from it
Args:
parser (:obj:DiamondParser): parser object with annotated reads
metric (str): scoring metric (efpkg by default)
|
lib/fama/output/krona_xml_writer.py
|
make_functions_chart
|
aekazakov/FamaProfiling
| 0 |
python
|
def make_functions_chart(parser, metric='efpkg'):
'Writes XML file for functions chart and generates Krona plot from it\n\n Args:\n parser (:obj:DiamondParser): parser object with annotated reads\n metric (str): scoring metric (efpkg by default)\n '
outfile = os.path.join(parser.options.get_project_dir(parser.sample.sample_id), parser.options.get_output_subdir(parser.sample.sample_id), ((((parser.sample.sample_id + '_') + parser.end) + '_') + parser.options.xml_name))
with open(outfile, 'w') as out:
if (metric == 'proteincount'):
metric = 'readcount'
out.write((((((('<krona key="false">\n' + '\t<attributes magnitude="') + metric) + '">\n') + '\t\t<attribute display="Protein count">') + metric) + '</attribute>\n'))
else:
out.write((((('<krona key="false">\n' + '\t<attributes magnitude="') + metric) + '">\n') + '\t\t<attribute display="Read count">readcount</attribute>\n'))
if (metric != 'readcount'):
out.write((((('\t\t<attribute display="Score:' + metric) + '">') + metric) + '</attribute>\n'))
out.write(((((('\t\t<attribute display="AAI %" mono="true">identity</attribute>\n' + '\t</attributes>\n') + ' '.join(['\t<color attribute="identity"', 'valueStart="50"', 'valueEnd="100"', 'hueStart="0"', 'hueEnd="240"', 'default="true"></color>\n'])) + '\t<datasets>\n\t\t<dataset>') + parser.sample.sample_id) + '</dataset>\n\t</datasets>\n'))
read_count = 0
total_rpkm = 0.0
groups_rpkm = defaultdict(float)
groups_counts = defaultdict(set)
groups_identity = defaultdict(list)
functions_counts = defaultdict(set)
functions_rpkm = defaultdict(float)
functions_identity = defaultdict(list)
for (_, read) in parser.reads.items():
if (read.status == STATUS_GOOD):
read_count += 1
for function in read.functions:
total_rpkm += read.functions[function]
groups_counts[parser.ref_data.lookup_function_group(function)].add(read.read_id)
functions_rpkm[function] += read.functions[function]
groups_rpkm[parser.ref_data.lookup_function_group(function)] += read.functions[function]
functions_counts[function].add(read.read_id)
for hit in read.hit_list.hits:
for function in hit.functions:
functions_identity[function].append(hit.identity)
groups_identity[parser.ref_data.lookup_function_group(function)].append(hit.identity)
out.write((((('\t<node name="' + parser.sample.sample_id) + '_') + parser.end) + '">\n'))
if (metric != 'readcount'):
out.write((('\t\t<readcount><val>' + str(read_count)) + '</val></readcount>\n'))
out.write((((((('\t\t<' + metric) + '><val>') + str(total_rpkm)) + '</val></') + metric) + '>\n'))
for group in groups_rpkm:
out.write((('\t\t<node name="' + group) + '">\n'))
if (metric != 'readcount'):
out.write((('\t\t\t<readcount><val>' + str(len(groups_counts[group]))) + '</val></readcount>\n'))
out.write((((((('\t\t\t<' + metric) + '><val>') + str(groups_rpkm[group])) + '</val></') + metric) + '>\n'))
if (group in groups_identity):
out.write((('\t\t\t<identity><val>' + str((sum(groups_identity[group]) / len(groups_identity[group])))) + '</val></identity>\n'))
else:
out.write('\t\t\t<identity><val>0.0</val></identity>\n')
for function in parser.ref_data.get_functions_in_group(group):
if (function in functions_rpkm):
out.write((('\t\t\t<node name="' + function) + '">\n'))
if (metric != 'readcount'):
out.write((('\t\t\t\t<readcount><val>' + str(len(functions_counts[function]))) + '</val></readcount>\n'))
out.write((((((('\t\t\t\t<' + metric) + '><val>') + str(functions_rpkm[function])) + '</val></') + metric) + '>\n'))
if (function in functions_identity):
out.write((('\t\t\t\t<identity><val>' + str((sum(functions_identity[function]) / len(functions_identity[function])))) + '</val></identity>\n'))
else:
out.write('\t\t\t\t<identity><val>0.0</val></identity>\n')
out.write('\t\t\t</node>\n')
out.write('\t\t</node>\n')
out.write('\t</node>\n</krona>')
html_file = os.path.join(parser.options.get_project_dir(parser.sample.sample_id), parser.options.get_output_subdir(parser.sample.sample_id), ((((parser.sample.sample_id + '_') + parser.end) + '_') + parser.options.html_name))
run_external_program([parser.config.krona_path, '-o', html_file, outfile])
|
def make_functions_chart(parser, metric='efpkg'):
'Writes XML file for functions chart and generates Krona plot from it\n\n Args:\n parser (:obj:DiamondParser): parser object with annotated reads\n metric (str): scoring metric (efpkg by default)\n '
outfile = os.path.join(parser.options.get_project_dir(parser.sample.sample_id), parser.options.get_output_subdir(parser.sample.sample_id), ((((parser.sample.sample_id + '_') + parser.end) + '_') + parser.options.xml_name))
with open(outfile, 'w') as out:
if (metric == 'proteincount'):
metric = 'readcount'
out.write((((((('<krona key="false">\n' + '\t<attributes magnitude="') + metric) + '">\n') + '\t\t<attribute display="Protein count">') + metric) + '</attribute>\n'))
else:
out.write((((('<krona key="false">\n' + '\t<attributes magnitude="') + metric) + '">\n') + '\t\t<attribute display="Read count">readcount</attribute>\n'))
if (metric != 'readcount'):
out.write((((('\t\t<attribute display="Score:' + metric) + '">') + metric) + '</attribute>\n'))
out.write(((((('\t\t<attribute display="AAI %" mono="true">identity</attribute>\n' + '\t</attributes>\n') + ' '.join(['\t<color attribute="identity"', 'valueStart="50"', 'valueEnd="100"', 'hueStart="0"', 'hueEnd="240"', 'default="true"></color>\n'])) + '\t<datasets>\n\t\t<dataset>') + parser.sample.sample_id) + '</dataset>\n\t</datasets>\n'))
read_count = 0
total_rpkm = 0.0
groups_rpkm = defaultdict(float)
groups_counts = defaultdict(set)
groups_identity = defaultdict(list)
functions_counts = defaultdict(set)
functions_rpkm = defaultdict(float)
functions_identity = defaultdict(list)
for (_, read) in parser.reads.items():
if (read.status == STATUS_GOOD):
read_count += 1
for function in read.functions:
total_rpkm += read.functions[function]
groups_counts[parser.ref_data.lookup_function_group(function)].add(read.read_id)
functions_rpkm[function] += read.functions[function]
groups_rpkm[parser.ref_data.lookup_function_group(function)] += read.functions[function]
functions_counts[function].add(read.read_id)
for hit in read.hit_list.hits:
for function in hit.functions:
functions_identity[function].append(hit.identity)
groups_identity[parser.ref_data.lookup_function_group(function)].append(hit.identity)
out.write((((('\t<node name="' + parser.sample.sample_id) + '_') + parser.end) + '">\n'))
if (metric != 'readcount'):
out.write((('\t\t<readcount><val>' + str(read_count)) + '</val></readcount>\n'))
out.write((((((('\t\t<' + metric) + '><val>') + str(total_rpkm)) + '</val></') + metric) + '>\n'))
for group in groups_rpkm:
out.write((('\t\t<node name="' + group) + '">\n'))
if (metric != 'readcount'):
out.write((('\t\t\t<readcount><val>' + str(len(groups_counts[group]))) + '</val></readcount>\n'))
out.write((((((('\t\t\t<' + metric) + '><val>') + str(groups_rpkm[group])) + '</val></') + metric) + '>\n'))
if (group in groups_identity):
out.write((('\t\t\t<identity><val>' + str((sum(groups_identity[group]) / len(groups_identity[group])))) + '</val></identity>\n'))
else:
out.write('\t\t\t<identity><val>0.0</val></identity>\n')
for function in parser.ref_data.get_functions_in_group(group):
if (function in functions_rpkm):
out.write((('\t\t\t<node name="' + function) + '">\n'))
if (metric != 'readcount'):
out.write((('\t\t\t\t<readcount><val>' + str(len(functions_counts[function]))) + '</val></readcount>\n'))
out.write((((((('\t\t\t\t<' + metric) + '><val>') + str(functions_rpkm[function])) + '</val></') + metric) + '>\n'))
if (function in functions_identity):
out.write((('\t\t\t\t<identity><val>' + str((sum(functions_identity[function]) / len(functions_identity[function])))) + '</val></identity>\n'))
else:
out.write('\t\t\t\t<identity><val>0.0</val></identity>\n')
out.write('\t\t\t</node>\n')
out.write('\t\t</node>\n')
out.write('\t</node>\n</krona>')
html_file = os.path.join(parser.options.get_project_dir(parser.sample.sample_id), parser.options.get_output_subdir(parser.sample.sample_id), ((((parser.sample.sample_id + '_') + parser.end) + '_') + parser.options.html_name))
run_external_program([parser.config.krona_path, '-o', html_file, outfile])<|docstring|>Writes XML file for functions chart and generates Krona plot from it
Args:
parser (:obj:DiamondParser): parser object with annotated reads
metric (str): scoring metric (efpkg by default)<|endoftext|>
|
1e329a023b4c0824cceea67d0fa57787dc07bbc2947a84001838ddb2adaac801
|
def get_taxon_xml(tax_profile, taxid, offset, metric='efpkg'):
"Returns XML node for a phylogenetic tree node and all its children\n\n Args:\n tax_profile (:obj:TaxonomyProfile): taxonomy profile\n taxid (str): taxonomy identifier of a node of interest\n offset (int): number of starting tabs\n metric (str): scoring metric (default value 'efpkg')\n\n Returns:\n ret_val (str): XML node\n "
if (taxid not in tax_profile.tree.data):
raise KeyError(taxid, 'not found in the tree!!!')
ret_val = (((('\t' * offset) + '<node name="') + tax_profile.tree.data[taxid].name) + '">\n')
offset += 1
if tax_profile.tree.data[taxid].attributes:
if (metric != 'readcount'):
ret_val += (((('\t' * offset) + '<readcount><val>') + format(tax_profile.tree.data[taxid].attributes['count'], '0.0f')) + '</val></readcount>\n')
ret_val += (((((((('\t' * offset) + '<') + metric) + '><val>') + format(tax_profile.tree.data[taxid].attributes[metric], '0.2f')) + '</val></') + metric) + '>\n')
ret_val += (((('\t' * offset) + '<identity><val>') + format((tax_profile.tree.data[taxid].attributes['identity'] / tax_profile.tree.data[taxid].attributes['hit_count']), '0.1f')) + '</val></identity>\n')
else:
if (metric != 'readcount'):
ret_val += (('\t' * offset) + '<readcount><val>0</val></readcount>\n')
ret_val += (((((('\t' * offset) + '<') + metric) + '><val>0.0</val></') + metric) + '>\n')
ret_val += (('\t' * offset) + '<identity><val>0.0</val></identity>\n')
if tax_profile.tree.data[taxid].children:
for child_taxid in tax_profile.tree.data[taxid].children:
ret_val += get_taxon_xml(tax_profile, child_taxid, offset, metric)
offset -= 1
ret_val += (('\t' * offset) + '</node>\n')
return ret_val
|
Returns XML node for a phylogenetic tree node and all its children
Args:
tax_profile (:obj:TaxonomyProfile): taxonomy profile
taxid (str): taxonomy identifier of a node of interest
offset (int): number of starting tabs
metric (str): scoring metric (default value 'efpkg')
Returns:
ret_val (str): XML node
|
lib/fama/output/krona_xml_writer.py
|
get_taxon_xml
|
aekazakov/FamaProfiling
| 0 |
python
|
def get_taxon_xml(tax_profile, taxid, offset, metric='efpkg'):
"Returns XML node for a phylogenetic tree node and all its children\n\n Args:\n tax_profile (:obj:TaxonomyProfile): taxonomy profile\n taxid (str): taxonomy identifier of a node of interest\n offset (int): number of starting tabs\n metric (str): scoring metric (default value 'efpkg')\n\n Returns:\n ret_val (str): XML node\n "
if (taxid not in tax_profile.tree.data):
raise KeyError(taxid, 'not found in the tree!!!')
ret_val = (((('\t' * offset) + '<node name="') + tax_profile.tree.data[taxid].name) + '">\n')
offset += 1
if tax_profile.tree.data[taxid].attributes:
if (metric != 'readcount'):
ret_val += (((('\t' * offset) + '<readcount><val>') + format(tax_profile.tree.data[taxid].attributes['count'], '0.0f')) + '</val></readcount>\n')
ret_val += (((((((('\t' * offset) + '<') + metric) + '><val>') + format(tax_profile.tree.data[taxid].attributes[metric], '0.2f')) + '</val></') + metric) + '>\n')
ret_val += (((('\t' * offset) + '<identity><val>') + format((tax_profile.tree.data[taxid].attributes['identity'] / tax_profile.tree.data[taxid].attributes['hit_count']), '0.1f')) + '</val></identity>\n')
else:
if (metric != 'readcount'):
ret_val += (('\t' * offset) + '<readcount><val>0</val></readcount>\n')
ret_val += (((((('\t' * offset) + '<') + metric) + '><val>0.0</val></') + metric) + '>\n')
ret_val += (('\t' * offset) + '<identity><val>0.0</val></identity>\n')
if tax_profile.tree.data[taxid].children:
for child_taxid in tax_profile.tree.data[taxid].children:
ret_val += get_taxon_xml(tax_profile, child_taxid, offset, metric)
offset -= 1
ret_val += (('\t' * offset) + '</node>\n')
return ret_val
|
def get_taxon_xml(tax_profile, taxid, offset, metric='efpkg'):
"Returns XML node for a phylogenetic tree node and all its children\n\n Args:\n tax_profile (:obj:TaxonomyProfile): taxonomy profile\n taxid (str): taxonomy identifier of a node of interest\n offset (int): number of starting tabs\n metric (str): scoring metric (default value 'efpkg')\n\n Returns:\n ret_val (str): XML node\n "
if (taxid not in tax_profile.tree.data):
raise KeyError(taxid, 'not found in the tree!!!')
ret_val = (((('\t' * offset) + '<node name="') + tax_profile.tree.data[taxid].name) + '">\n')
offset += 1
if tax_profile.tree.data[taxid].attributes:
if (metric != 'readcount'):
ret_val += (((('\t' * offset) + '<readcount><val>') + format(tax_profile.tree.data[taxid].attributes['count'], '0.0f')) + '</val></readcount>\n')
ret_val += (((((((('\t' * offset) + '<') + metric) + '><val>') + format(tax_profile.tree.data[taxid].attributes[metric], '0.2f')) + '</val></') + metric) + '>\n')
ret_val += (((('\t' * offset) + '<identity><val>') + format((tax_profile.tree.data[taxid].attributes['identity'] / tax_profile.tree.data[taxid].attributes['hit_count']), '0.1f')) + '</val></identity>\n')
else:
if (metric != 'readcount'):
ret_val += (('\t' * offset) + '<readcount><val>0</val></readcount>\n')
ret_val += (((((('\t' * offset) + '<') + metric) + '><val>0.0</val></') + metric) + '>\n')
ret_val += (('\t' * offset) + '<identity><val>0.0</val></identity>\n')
if tax_profile.tree.data[taxid].children:
for child_taxid in tax_profile.tree.data[taxid].children:
ret_val += get_taxon_xml(tax_profile, child_taxid, offset, metric)
offset -= 1
ret_val += (('\t' * offset) + '</node>\n')
return ret_val<|docstring|>Returns XML node for a phylogenetic tree node and all its children
Args:
tax_profile (:obj:TaxonomyProfile): taxonomy profile
taxid (str): taxonomy identifier of a node of interest
offset (int): number of starting tabs
metric (str): scoring metric (default value 'efpkg')
Returns:
ret_val (str): XML node<|endoftext|>
|
f7c4f1290f218906aa37d74741d63b42d7aabc753a94264b8f5d47a691e5b428
|
def get_lca_tax_xml(tax_profile, taxid, offset, metric='efpkg'):
'Returns XML node for a phylogenetic tree node and all its children.\n Creates additional child node for a fictional "Unclassified..." taxon\n if not all reads of the current node are mapped to children nodes.\n\n Args:\n tax_profile (:obj:TaxonomyProfile): taxonomy profile\n taxid (str): taxonomy identifier of a node of interest\n offset (int): number of starting tabs\n metric (str): scoring metric (default value \'efpkg\')\n\n Returns:\n ret_val (str): XML node\n '
attribute_values = defaultdict(float)
try:
ret_val = (((('\t' * offset) + '<node name="') + tax_profile.tree.data[taxid].name) + '">\n')
except KeyError:
print(taxid, 'not found in the tree data!!!')
raise KeyError
offset += 1
if tax_profile.tree.data[taxid].attributes:
if ((metric != 'readcount') and (metric != 'proteincount')):
ret_val += (((('\t' * offset) + '<readcount><val>') + format(tax_profile.tree.data[taxid].attributes['count'], '0.0f')) + '</val></readcount>\n')
ret_val += (((((((('\t' * offset) + '<') + metric) + '><val>') + format(tax_profile.tree.data[taxid].attributes[metric], '0.2f')) + '</val></') + metric) + '>\n')
ret_val += (((('\t' * offset) + '<identity><val>') + format((tax_profile.tree.data[taxid].attributes['identity'] / tax_profile.tree.data[taxid].attributes['hit_count']), '0.1f')) + '</val></identity>\n')
else:
if ((metric != 'readcount') and (metric != 'proteincount')):
ret_val += (('\t' * offset) + '<readcount><val>0</val></readcount>\n')
ret_val += (((((('\t' * offset) + '<') + metric) + '><val>0.0</val></') + metric) + '>\n')
ret_val += (('\t' * offset) + '<identity><val>0.0</val></identity>\n')
if tax_profile.tree.data[taxid].children:
for child_taxid in tax_profile.tree.data[taxid].children:
(child_node, child_values) = get_lca_tax_xml(tax_profile, child_taxid, offset, metric)
ret_val += child_node
for (key, val) in child_values.items():
attribute_values[key] += val
if (tax_profile.tree.data[taxid].attributes and (attribute_values['count'] < tax_profile.tree.data[taxid].attributes['count'])):
unknown_node = ('Unidentified ' + tax_profile.tree.data[taxid].name)
if (offset == 2):
unknown_node = 'Unknown'
ret_val += (((('\t' * offset) + '<node name="') + unknown_node) + '">\n')
offset += 1
if ((metric != 'readcount') and (metric != 'proteincount')):
ret_val += (((('\t' * offset) + '<readcount><val>') + format((tax_profile.tree.data[taxid].attributes['count'] - attribute_values['count']), '0.0f')) + '</val></readcount>\n')
ret_val += (((((((('\t' * offset) + '<') + metric) + '><val>') + format((tax_profile.tree.data[taxid].attributes[metric] - attribute_values[metric]), '0.2f')) + '</val></') + metric) + '>\n')
if (tax_profile.tree.data[taxid].attributes['hit_count'] > attribute_values['hit_count']):
ret_val += (((('\t' * offset) + '<identity><val>') + format(((tax_profile.tree.data[taxid].attributes['identity'] - attribute_values['identity']) / (tax_profile.tree.data[taxid].attributes['hit_count'] - attribute_values['hit_count'])), '0.1f')) + '</val></identity>\n')
else:
ret_val += (('\t' * offset) + '<identity><val>0.0</val></identity>\n')
offset -= 1
ret_val += (('\t' * offset) + '</node>\n')
offset -= 1
ret_val += (('\t' * offset) + '</node>\n')
attribute_values = defaultdict(float)
attribute_values[metric] = tax_profile.tree.data[taxid].attributes[metric]
attribute_values['count'] = tax_profile.tree.data[taxid].attributes['count']
attribute_values['identity'] = tax_profile.tree.data[taxid].attributes['identity']
attribute_values['hit_count'] = tax_profile.tree.data[taxid].attributes['hit_count']
return (ret_val, attribute_values)
|
Returns XML node for a phylogenetic tree node and all its children.
Creates additional child node for a fictional "Unclassified..." taxon
if not all reads of the current node are mapped to children nodes.
Args:
tax_profile (:obj:TaxonomyProfile): taxonomy profile
taxid (str): taxonomy identifier of a node of interest
offset (int): number of starting tabs
metric (str): scoring metric (default value 'efpkg')
Returns:
ret_val (str): XML node
|
lib/fama/output/krona_xml_writer.py
|
get_lca_tax_xml
|
aekazakov/FamaProfiling
| 0 |
python
|
def get_lca_tax_xml(tax_profile, taxid, offset, metric='efpkg'):
'Returns XML node for a phylogenetic tree node and all its children.\n Creates additional child node for a fictional "Unclassified..." taxon\n if not all reads of the current node are mapped to children nodes.\n\n Args:\n tax_profile (:obj:TaxonomyProfile): taxonomy profile\n taxid (str): taxonomy identifier of a node of interest\n offset (int): number of starting tabs\n metric (str): scoring metric (default value \'efpkg\')\n\n Returns:\n ret_val (str): XML node\n '
attribute_values = defaultdict(float)
try:
ret_val = (((('\t' * offset) + '<node name="') + tax_profile.tree.data[taxid].name) + '">\n')
except KeyError:
print(taxid, 'not found in the tree data!!!')
raise KeyError
offset += 1
if tax_profile.tree.data[taxid].attributes:
if ((metric != 'readcount') and (metric != 'proteincount')):
ret_val += (((('\t' * offset) + '<readcount><val>') + format(tax_profile.tree.data[taxid].attributes['count'], '0.0f')) + '</val></readcount>\n')
ret_val += (((((((('\t' * offset) + '<') + metric) + '><val>') + format(tax_profile.tree.data[taxid].attributes[metric], '0.2f')) + '</val></') + metric) + '>\n')
ret_val += (((('\t' * offset) + '<identity><val>') + format((tax_profile.tree.data[taxid].attributes['identity'] / tax_profile.tree.data[taxid].attributes['hit_count']), '0.1f')) + '</val></identity>\n')
else:
if ((metric != 'readcount') and (metric != 'proteincount')):
ret_val += (('\t' * offset) + '<readcount><val>0</val></readcount>\n')
ret_val += (((((('\t' * offset) + '<') + metric) + '><val>0.0</val></') + metric) + '>\n')
ret_val += (('\t' * offset) + '<identity><val>0.0</val></identity>\n')
if tax_profile.tree.data[taxid].children:
for child_taxid in tax_profile.tree.data[taxid].children:
(child_node, child_values) = get_lca_tax_xml(tax_profile, child_taxid, offset, metric)
ret_val += child_node
for (key, val) in child_values.items():
attribute_values[key] += val
if (tax_profile.tree.data[taxid].attributes and (attribute_values['count'] < tax_profile.tree.data[taxid].attributes['count'])):
unknown_node = ('Unidentified ' + tax_profile.tree.data[taxid].name)
if (offset == 2):
unknown_node = 'Unknown'
ret_val += (((('\t' * offset) + '<node name="') + unknown_node) + '">\n')
offset += 1
if ((metric != 'readcount') and (metric != 'proteincount')):
ret_val += (((('\t' * offset) + '<readcount><val>') + format((tax_profile.tree.data[taxid].attributes['count'] - attribute_values['count']), '0.0f')) + '</val></readcount>\n')
ret_val += (((((((('\t' * offset) + '<') + metric) + '><val>') + format((tax_profile.tree.data[taxid].attributes[metric] - attribute_values[metric]), '0.2f')) + '</val></') + metric) + '>\n')
if (tax_profile.tree.data[taxid].attributes['hit_count'] > attribute_values['hit_count']):
ret_val += (((('\t' * offset) + '<identity><val>') + format(((tax_profile.tree.data[taxid].attributes['identity'] - attribute_values['identity']) / (tax_profile.tree.data[taxid].attributes['hit_count'] - attribute_values['hit_count'])), '0.1f')) + '</val></identity>\n')
else:
ret_val += (('\t' * offset) + '<identity><val>0.0</val></identity>\n')
offset -= 1
ret_val += (('\t' * offset) + '</node>\n')
offset -= 1
ret_val += (('\t' * offset) + '</node>\n')
attribute_values = defaultdict(float)
attribute_values[metric] = tax_profile.tree.data[taxid].attributes[metric]
attribute_values['count'] = tax_profile.tree.data[taxid].attributes['count']
attribute_values['identity'] = tax_profile.tree.data[taxid].attributes['identity']
attribute_values['hit_count'] = tax_profile.tree.data[taxid].attributes['hit_count']
return (ret_val, attribute_values)
|
def get_lca_tax_xml(tax_profile, taxid, offset, metric='efpkg'):
'Returns XML node for a phylogenetic tree node and all its children.\n Creates additional child node for a fictional "Unclassified..." taxon\n if not all reads of the current node are mapped to children nodes.\n\n Args:\n tax_profile (:obj:TaxonomyProfile): taxonomy profile\n taxid (str): taxonomy identifier of a node of interest\n offset (int): number of starting tabs\n metric (str): scoring metric (default value \'efpkg\')\n\n Returns:\n ret_val (str): XML node\n '
attribute_values = defaultdict(float)
try:
ret_val = (((('\t' * offset) + '<node name="') + tax_profile.tree.data[taxid].name) + '">\n')
except KeyError:
print(taxid, 'not found in the tree data!!!')
raise KeyError
offset += 1
if tax_profile.tree.data[taxid].attributes:
if ((metric != 'readcount') and (metric != 'proteincount')):
ret_val += (((('\t' * offset) + '<readcount><val>') + format(tax_profile.tree.data[taxid].attributes['count'], '0.0f')) + '</val></readcount>\n')
ret_val += (((((((('\t' * offset) + '<') + metric) + '><val>') + format(tax_profile.tree.data[taxid].attributes[metric], '0.2f')) + '</val></') + metric) + '>\n')
ret_val += (((('\t' * offset) + '<identity><val>') + format((tax_profile.tree.data[taxid].attributes['identity'] / tax_profile.tree.data[taxid].attributes['hit_count']), '0.1f')) + '</val></identity>\n')
else:
if ((metric != 'readcount') and (metric != 'proteincount')):
ret_val += (('\t' * offset) + '<readcount><val>0</val></readcount>\n')
ret_val += (((((('\t' * offset) + '<') + metric) + '><val>0.0</val></') + metric) + '>\n')
ret_val += (('\t' * offset) + '<identity><val>0.0</val></identity>\n')
if tax_profile.tree.data[taxid].children:
for child_taxid in tax_profile.tree.data[taxid].children:
(child_node, child_values) = get_lca_tax_xml(tax_profile, child_taxid, offset, metric)
ret_val += child_node
for (key, val) in child_values.items():
attribute_values[key] += val
if (tax_profile.tree.data[taxid].attributes and (attribute_values['count'] < tax_profile.tree.data[taxid].attributes['count'])):
unknown_node = ('Unidentified ' + tax_profile.tree.data[taxid].name)
if (offset == 2):
unknown_node = 'Unknown'
ret_val += (((('\t' * offset) + '<node name="') + unknown_node) + '">\n')
offset += 1
if ((metric != 'readcount') and (metric != 'proteincount')):
ret_val += (((('\t' * offset) + '<readcount><val>') + format((tax_profile.tree.data[taxid].attributes['count'] - attribute_values['count']), '0.0f')) + '</val></readcount>\n')
ret_val += (((((((('\t' * offset) + '<') + metric) + '><val>') + format((tax_profile.tree.data[taxid].attributes[metric] - attribute_values[metric]), '0.2f')) + '</val></') + metric) + '>\n')
if (tax_profile.tree.data[taxid].attributes['hit_count'] > attribute_values['hit_count']):
ret_val += (((('\t' * offset) + '<identity><val>') + format(((tax_profile.tree.data[taxid].attributes['identity'] - attribute_values['identity']) / (tax_profile.tree.data[taxid].attributes['hit_count'] - attribute_values['hit_count'])), '0.1f')) + '</val></identity>\n')
else:
ret_val += (('\t' * offset) + '<identity><val>0.0</val></identity>\n')
offset -= 1
ret_val += (('\t' * offset) + '</node>\n')
offset -= 1
ret_val += (('\t' * offset) + '</node>\n')
attribute_values = defaultdict(float)
attribute_values[metric] = tax_profile.tree.data[taxid].attributes[metric]
attribute_values['count'] = tax_profile.tree.data[taxid].attributes['count']
attribute_values['identity'] = tax_profile.tree.data[taxid].attributes['identity']
attribute_values['hit_count'] = tax_profile.tree.data[taxid].attributes['hit_count']
return (ret_val, attribute_values)<|docstring|>Returns XML node for a phylogenetic tree node and all its children.
Creates additional child node for a fictional "Unclassified..." taxon
if not all reads of the current node are mapped to children nodes.
Args:
tax_profile (:obj:TaxonomyProfile): taxonomy profile
taxid (str): taxonomy identifier of a node of interest
offset (int): number of starting tabs
metric (str): scoring metric (default value 'efpkg')
Returns:
ret_val (str): XML node<|endoftext|>
|
6c19fc664aadbc4ffda3b9f2b473b004e625208e2781885effd2819c7b11e900
|
def make_taxonomy_chart(tax_profile, sample, outfile, krona_path, metric='efpkg'):
'Writes XML file for taxonomy chart of one sample and generates Krona plot from it\n\n Args:\n tax_profile (:obj:TaxonomyProfile): taxonomy profile object\n sample (str): sample identifier\n outfile (str): path for XML output\n krona_path (str): Krona Tools command\n metric (str): scoring metric (efpkg by default)\n '
with open(outfile, 'w') as out:
out.write('<krona key="false">\n')
out.write((('\t<attributes magnitude="' + metric) + '">\n'))
if (metric == 'proteincount'):
out.write((('\t\t<attribute display="Protein count">' + metric) + '</attribute>\n'))
else:
out.write('\t\t<attribute display="Read count">readcount</attribute>\n')
if ((metric != 'readcount') and (metric != 'proteincount')):
out.write((((('\t\t<attribute display="Score:' + metric) + '">') + metric) + '</attribute>\n'))
out.write('\t\t<attribute display="AAI %" mono="true">identity</attribute>\n')
out.write('\t</attributes>\n')
out.write(('\t<color attribute="identity" valueStart="50" valueEnd="100" hueStart="0"' + ' hueEnd="240" default="true"></color>\n'))
out.write('\t<datasets>\n')
out.write((('\t\t<dataset>' + sample) + '</dataset>\n'))
out.write('\t</datasets>\n')
offset = 1
(child_node, _) = get_lca_tax_xml(tax_profile, ROOT_TAXONOMY_ID, offset, metric=metric)
out.write(child_node)
out.write('</krona>')
html_file = (outfile + '.html')
krona_cmd = [krona_path, '-o', html_file, outfile]
run_external_program(krona_cmd)
|
Writes XML file for taxonomy chart of one sample and generates Krona plot from it
Args:
tax_profile (:obj:TaxonomyProfile): taxonomy profile object
sample (str): sample identifier
outfile (str): path for XML output
krona_path (str): Krona Tools command
metric (str): scoring metric (efpkg by default)
|
lib/fama/output/krona_xml_writer.py
|
make_taxonomy_chart
|
aekazakov/FamaProfiling
| 0 |
python
|
def make_taxonomy_chart(tax_profile, sample, outfile, krona_path, metric='efpkg'):
'Writes XML file for taxonomy chart of one sample and generates Krona plot from it\n\n Args:\n tax_profile (:obj:TaxonomyProfile): taxonomy profile object\n sample (str): sample identifier\n outfile (str): path for XML output\n krona_path (str): Krona Tools command\n metric (str): scoring metric (efpkg by default)\n '
with open(outfile, 'w') as out:
out.write('<krona key="false">\n')
out.write((('\t<attributes magnitude="' + metric) + '">\n'))
if (metric == 'proteincount'):
out.write((('\t\t<attribute display="Protein count">' + metric) + '</attribute>\n'))
else:
out.write('\t\t<attribute display="Read count">readcount</attribute>\n')
if ((metric != 'readcount') and (metric != 'proteincount')):
out.write((((('\t\t<attribute display="Score:' + metric) + '">') + metric) + '</attribute>\n'))
out.write('\t\t<attribute display="AAI %" mono="true">identity</attribute>\n')
out.write('\t</attributes>\n')
out.write(('\t<color attribute="identity" valueStart="50" valueEnd="100" hueStart="0"' + ' hueEnd="240" default="true"></color>\n'))
out.write('\t<datasets>\n')
out.write((('\t\t<dataset>' + sample) + '</dataset>\n'))
out.write('\t</datasets>\n')
offset = 1
(child_node, _) = get_lca_tax_xml(tax_profile, ROOT_TAXONOMY_ID, offset, metric=metric)
out.write(child_node)
out.write('</krona>')
html_file = (outfile + '.html')
krona_cmd = [krona_path, '-o', html_file, outfile]
run_external_program(krona_cmd)
|
def make_taxonomy_chart(tax_profile, sample, outfile, krona_path, metric='efpkg'):
'Writes XML file for taxonomy chart of one sample and generates Krona plot from it\n\n Args:\n tax_profile (:obj:TaxonomyProfile): taxonomy profile object\n sample (str): sample identifier\n outfile (str): path for XML output\n krona_path (str): Krona Tools command\n metric (str): scoring metric (efpkg by default)\n '
with open(outfile, 'w') as out:
out.write('<krona key="false">\n')
out.write((('\t<attributes magnitude="' + metric) + '">\n'))
if (metric == 'proteincount'):
out.write((('\t\t<attribute display="Protein count">' + metric) + '</attribute>\n'))
else:
out.write('\t\t<attribute display="Read count">readcount</attribute>\n')
if ((metric != 'readcount') and (metric != 'proteincount')):
out.write((((('\t\t<attribute display="Score:' + metric) + '">') + metric) + '</attribute>\n'))
out.write('\t\t<attribute display="AAI %" mono="true">identity</attribute>\n')
out.write('\t</attributes>\n')
out.write(('\t<color attribute="identity" valueStart="50" valueEnd="100" hueStart="0"' + ' hueEnd="240" default="true"></color>\n'))
out.write('\t<datasets>\n')
out.write((('\t\t<dataset>' + sample) + '</dataset>\n'))
out.write('\t</datasets>\n')
offset = 1
(child_node, _) = get_lca_tax_xml(tax_profile, ROOT_TAXONOMY_ID, offset, metric=metric)
out.write(child_node)
out.write('</krona>')
html_file = (outfile + '.html')
krona_cmd = [krona_path, '-o', html_file, outfile]
run_external_program(krona_cmd)<|docstring|>Writes XML file for taxonomy chart of one sample and generates Krona plot from it
Args:
tax_profile (:obj:TaxonomyProfile): taxonomy profile object
sample (str): sample identifier
outfile (str): path for XML output
krona_path (str): Krona Tools command
metric (str): scoring metric (efpkg by default)<|endoftext|>
|
e6ac0df04a67d25d55d64040f3df20019b861974789a269c77179a23b06737d3
|
def make_taxonomy_series_chart(tax_profile, sample_list, outfile, krona_path, metric='efpkg'):
'Writes XML file for taxonomy chart of multiple samples and generates Krona plot for it.\n Taxonomy profile must have two-level attributes, with function identifier as outer key and\n a metric as inner key.\n\n Args:\n tax_profile (:obj:TaxonomyProfile): taxonomy profile object\n sample_list (list of str): sample identifiers\n outfile (str): path for XML output\n krona_path (str): Krona Tools command\n metric (str): scoring metric (efpkg by default)\n '
with open(outfile, 'w') as out:
out.write('<krona key="false">\n')
out.write((('\t<attributes magnitude="' + metric) + '">\n'))
if (metric == 'proteincount'):
out.write((('\t\t<attribute display="Protein count">' + metric) + '</attribute>\n'))
else:
out.write('\t\t<attribute display="Read count">readcount</attribute>\n')
if ((metric != 'readcount') and (metric != 'proteincount')):
out.write((((('\t\t<attribute display="Score:' + metric) + '">') + metric) + '</attribute>\n'))
out.write('\t\t<attribute display="AAI %" mono="true">identity</attribute>\n')
out.write('\t</attributes>\n')
out.write(('\t<color attribute="identity" valueStart="50" valueEnd="100" hueStart="0" ' + 'hueEnd="240" default="true"></color>\n'))
out.write('\t<datasets>\n')
for sample in sample_list:
out.write((('\t\t<dataset>' + sample) + '</dataset>\n'))
out.write('\t</datasets>\n')
offset = 1
(child_nodes, _) = get_lca_dataseries_tax_xml(tax_profile, sample_list, ROOT_TAXONOMY_ID, offset, metric=metric)
out.write(child_nodes)
out.write('</krona>')
html_file = (outfile + '.html')
krona_cmd = [krona_path, '-o', html_file, outfile]
run_external_program(krona_cmd)
|
Writes XML file for taxonomy chart of multiple samples and generates Krona plot for it.
Taxonomy profile must have two-level attributes, with function identifier as outer key and
a metric as inner key.
Args:
tax_profile (:obj:TaxonomyProfile): taxonomy profile object
sample_list (list of str): sample identifiers
outfile (str): path for XML output
krona_path (str): Krona Tools command
metric (str): scoring metric (efpkg by default)
|
lib/fama/output/krona_xml_writer.py
|
make_taxonomy_series_chart
|
aekazakov/FamaProfiling
| 0 |
python
|
def make_taxonomy_series_chart(tax_profile, sample_list, outfile, krona_path, metric='efpkg'):
'Writes XML file for taxonomy chart of multiple samples and generates Krona plot for it.\n Taxonomy profile must have two-level attributes, with function identifier as outer key and\n a metric as inner key.\n\n Args:\n tax_profile (:obj:TaxonomyProfile): taxonomy profile object\n sample_list (list of str): sample identifiers\n outfile (str): path for XML output\n krona_path (str): Krona Tools command\n metric (str): scoring metric (efpkg by default)\n '
with open(outfile, 'w') as out:
out.write('<krona key="false">\n')
out.write((('\t<attributes magnitude="' + metric) + '">\n'))
if (metric == 'proteincount'):
out.write((('\t\t<attribute display="Protein count">' + metric) + '</attribute>\n'))
else:
out.write('\t\t<attribute display="Read count">readcount</attribute>\n')
if ((metric != 'readcount') and (metric != 'proteincount')):
out.write((((('\t\t<attribute display="Score:' + metric) + '">') + metric) + '</attribute>\n'))
out.write('\t\t<attribute display="AAI %" mono="true">identity</attribute>\n')
out.write('\t</attributes>\n')
out.write(('\t<color attribute="identity" valueStart="50" valueEnd="100" hueStart="0" ' + 'hueEnd="240" default="true"></color>\n'))
out.write('\t<datasets>\n')
for sample in sample_list:
out.write((('\t\t<dataset>' + sample) + '</dataset>\n'))
out.write('\t</datasets>\n')
offset = 1
(child_nodes, _) = get_lca_dataseries_tax_xml(tax_profile, sample_list, ROOT_TAXONOMY_ID, offset, metric=metric)
out.write(child_nodes)
out.write('</krona>')
html_file = (outfile + '.html')
krona_cmd = [krona_path, '-o', html_file, outfile]
run_external_program(krona_cmd)
|
def make_taxonomy_series_chart(tax_profile, sample_list, outfile, krona_path, metric='efpkg'):
'Writes XML file for taxonomy chart of multiple samples and generates Krona plot for it.\n Taxonomy profile must have two-level attributes, with function identifier as outer key and\n a metric as inner key.\n\n Args:\n tax_profile (:obj:TaxonomyProfile): taxonomy profile object\n sample_list (list of str): sample identifiers\n outfile (str): path for XML output\n krona_path (str): Krona Tools command\n metric (str): scoring metric (efpkg by default)\n '
with open(outfile, 'w') as out:
out.write('<krona key="false">\n')
out.write((('\t<attributes magnitude="' + metric) + '">\n'))
if (metric == 'proteincount'):
out.write((('\t\t<attribute display="Protein count">' + metric) + '</attribute>\n'))
else:
out.write('\t\t<attribute display="Read count">readcount</attribute>\n')
if ((metric != 'readcount') and (metric != 'proteincount')):
out.write((((('\t\t<attribute display="Score:' + metric) + '">') + metric) + '</attribute>\n'))
out.write('\t\t<attribute display="AAI %" mono="true">identity</attribute>\n')
out.write('\t</attributes>\n')
out.write(('\t<color attribute="identity" valueStart="50" valueEnd="100" hueStart="0" ' + 'hueEnd="240" default="true"></color>\n'))
out.write('\t<datasets>\n')
for sample in sample_list:
out.write((('\t\t<dataset>' + sample) + '</dataset>\n'))
out.write('\t</datasets>\n')
offset = 1
(child_nodes, _) = get_lca_dataseries_tax_xml(tax_profile, sample_list, ROOT_TAXONOMY_ID, offset, metric=metric)
out.write(child_nodes)
out.write('</krona>')
html_file = (outfile + '.html')
krona_cmd = [krona_path, '-o', html_file, outfile]
run_external_program(krona_cmd)<|docstring|>Writes XML file for taxonomy chart of multiple samples and generates Krona plot for it.
Taxonomy profile must have two-level attributes, with function identifier as outer key and
a metric as inner key.
Args:
tax_profile (:obj:TaxonomyProfile): taxonomy profile object
sample_list (list of str): sample identifiers
outfile (str): path for XML output
krona_path (str): Krona Tools command
metric (str): scoring metric (efpkg by default)<|endoftext|>
|
ceae01c67116a9e04a9d16bca1751fdd8c41b39f4a240489f731960cfb520589
|
def get_lca_dataseries_tax_xml(tax_profile, dataseries, taxid, offset, metric='efpkg'):
'Returns XML node for a phylogenetic tree node and all its children.\n Creates additional child node for a fictional "Unclassified..." taxon\n if not all reads of the current node were mapped to children nodes.\n\n Args:\n tax_profile (:obj:TaxonomyProfile): taxonomy profile\n dataseries (list of str): either sample identifiers or function identifiers,\n depending on profile type (functional or taxonomic)\n taxid (str): taxonomy identifier of a node of interest\n offset (int): number of starting tabs\n metric (str): scoring metric (default value \'efpkg\')\n\n Returns:\n ret_val (str): XML node\n attribute_values (defaultdict[str,dict[str,float]]): outer key is\n one of dataseries members, inner key is in [metric, \'count\', \'identity\'\n \'hit_count\'], value is float.\n '
attribute_values = autovivify(2, float)
if (taxid not in tax_profile.tree.data):
raise KeyError(taxid, 'not found in the tree!!!')
ret_val = (((('\t' * offset) + '<node name="') + tax_profile.tree.data[taxid].name) + '">\n')
offset += 1
if tax_profile.tree.data[taxid].attributes:
if ((metric != 'readcount') and (metric != 'proteincount')):
ret_val += (('\t' * offset) + '<readcount>')
for datapoint in dataseries:
if ((datapoint in tax_profile.tree.data[taxid].attributes) and ('count' in tax_profile.tree.data[taxid].attributes[datapoint])):
ret_val += (('<val>' + format(tax_profile.tree.data[taxid].attributes[datapoint]['count'], '0.0f')) + '</val>')
else:
ret_val += '<val>0</val>'
ret_val += '</readcount>\n'
ret_val += (((('\t' * offset) + '<') + metric) + '>')
for datapoint in dataseries:
if ((datapoint in tax_profile.tree.data[taxid].attributes) and (metric in tax_profile.tree.data[taxid].attributes[datapoint])):
ret_val += (('<val>' + format(tax_profile.tree.data[taxid].attributes[datapoint][metric], '0.6f')) + '</val>')
else:
ret_val += '<val>0.0</val>'
ret_val += (((('</' + metric) + '>\n') + ('\t' * offset)) + '<identity>')
for datapoint in dataseries:
if ((datapoint in tax_profile.tree.data[taxid].attributes) and ('identity' in tax_profile.tree.data[taxid].attributes[datapoint])):
ret_val += (('<val>' + format((tax_profile.tree.data[taxid].attributes[datapoint]['identity'] / tax_profile.tree.data[taxid].attributes[datapoint]['hit_count']), '0.1f')) + '</val>')
else:
ret_val += '<val>0.0</val>'
ret_val += '</identity>\n'
else:
if ((metric != 'readcount') and (metric != 'proteincount')):
ret_val += (('\t' * offset) + '<readcount>')
ret_val += ('<val>0</val>' * len(dataseries))
ret_val += '</readcount>\n'
ret_val += (((('\t' * offset) + '<') + metric) + '>')
ret_val += ('<val>0.0</val>' * len(dataseries))
ret_val += (((('<' + metric) + '>\n') + ('\t' * offset)) + '<identity>')
ret_val += ('<val>0.0</val>' * len(dataseries))
ret_val += '</identity>\n'
if tax_profile.tree.data[taxid].children:
for child_taxid in tax_profile.tree.data[taxid].children:
(child_node, child_values) = get_lca_dataseries_tax_xml(tax_profile, dataseries, child_taxid, offset, metric=metric)
ret_val += child_node
for datapoint in child_values.keys():
for (key, val) in child_values[datapoint].items():
attribute_values[datapoint][key] += val
unidentified_flag = False
for datapoint in dataseries:
if (datapoint in tax_profile.tree.data[taxid].attributes):
if (attribute_values[datapoint]['count'] < tax_profile.tree.data[taxid].attributes[datapoint]['count']):
unidentified_flag = True
break
if unidentified_flag:
if (offset == 2):
ret_val += (('\t' * offset) + '<node name="Unclassified">\n')
else:
ret_val += (((('\t' * offset) + '<node name="Unclassified ') + tax_profile.tree.data[taxid].name) + '">\n')
offset += 1
if ((metric != 'readcount') and (metric != 'proteincount')):
ret_val += (('\t' * offset) + '<readcount>')
for datapoint in dataseries:
if ((datapoint in tax_profile.tree.data[taxid].attributes) and (attribute_values[datapoint]['count'] < tax_profile.tree.data[taxid].attributes[datapoint]['count'])):
ret_val += (('<val>' + format((tax_profile.tree.data[taxid].attributes[datapoint]['count'] - attribute_values[datapoint]['count']), '0.0f')) + '</val>')
else:
ret_val += '<val>0</val>'
ret_val += '</readcount>\n'
ret_val += (((('\t' * offset) + '<') + metric) + '>')
for datapoint in dataseries:
if ((datapoint in tax_profile.tree.data[taxid].attributes) and (attribute_values[datapoint]['count'] < tax_profile.tree.data[taxid].attributes[datapoint]['count'])):
ret_val += (('<val>' + format((tax_profile.tree.data[taxid].attributes[datapoint][metric] - attribute_values[datapoint][metric]), '0.6f')) + '</val>')
else:
ret_val += '<val>0.0</val>'
ret_val += (('</' + metric) + '>\n')
ret_val += (('\t' * offset) + '<identity>')
for datapoint in dataseries:
if ((datapoint in tax_profile.tree.data[taxid].attributes) and ('hit_count' in tax_profile.tree.data[taxid].attributes[datapoint]) and (attribute_values[datapoint]['hit_count'] < tax_profile.tree.data[taxid].attributes[datapoint]['hit_count'])):
ret_val += (('<val>' + format(((tax_profile.tree.data[taxid].attributes[datapoint]['identity'] - attribute_values[datapoint]['identity']) / (tax_profile.tree.data[taxid].attributes[datapoint]['hit_count'] - attribute_values[datapoint]['hit_count'])), '0.1f')) + '</val>')
else:
ret_val += '<val>0.0</val>'
ret_val += '</identity>\n'
offset -= 1
ret_val += (('\t' * offset) + '</node>\n')
offset -= 1
ret_val += (('\t' * offset) + '</node>\n')
attribute_values = autovivify(1)
for datapoint in dataseries:
if (datapoint in tax_profile.tree.data[taxid].attributes):
if (metric in tax_profile.tree.data[taxid].attributes[datapoint]):
attribute_values[datapoint][metric] = tax_profile.tree.data[taxid].attributes[datapoint][metric]
if ('count' in tax_profile.tree.data[taxid].attributes[datapoint]):
attribute_values[datapoint]['count'] = tax_profile.tree.data[taxid].attributes[datapoint]['count']
if ('identity' in tax_profile.tree.data[taxid].attributes[datapoint]):
attribute_values[datapoint]['identity'] = tax_profile.tree.data[taxid].attributes[datapoint]['identity']
if ('hit_count' in tax_profile.tree.data[taxid].attributes[datapoint]):
attribute_values[datapoint]['hit_count'] = tax_profile.tree.data[taxid].attributes[datapoint]['hit_count']
return (ret_val, attribute_values)
|
Returns XML node for a phylogenetic tree node and all its children.
Creates additional child node for a fictional "Unclassified..." taxon
if not all reads of the current node were mapped to children nodes.
Args:
tax_profile (:obj:TaxonomyProfile): taxonomy profile
dataseries (list of str): either sample identifiers or function identifiers,
depending on profile type (functional or taxonomic)
taxid (str): taxonomy identifier of a node of interest
offset (int): number of starting tabs
metric (str): scoring metric (default value 'efpkg')
Returns:
ret_val (str): XML node
attribute_values (defaultdict[str,dict[str,float]]): outer key is
one of dataseries members, inner key is in [metric, 'count', 'identity'
'hit_count'], value is float.
|
lib/fama/output/krona_xml_writer.py
|
get_lca_dataseries_tax_xml
|
aekazakov/FamaProfiling
| 0 |
python
|
def get_lca_dataseries_tax_xml(tax_profile, dataseries, taxid, offset, metric='efpkg'):
'Returns XML node for a phylogenetic tree node and all its children.\n Creates additional child node for a fictional "Unclassified..." taxon\n if not all reads of the current node were mapped to children nodes.\n\n Args:\n tax_profile (:obj:TaxonomyProfile): taxonomy profile\n dataseries (list of str): either sample identifiers or function identifiers,\n depending on profile type (functional or taxonomic)\n taxid (str): taxonomy identifier of a node of interest\n offset (int): number of starting tabs\n metric (str): scoring metric (default value \'efpkg\')\n\n Returns:\n ret_val (str): XML node\n attribute_values (defaultdict[str,dict[str,float]]): outer key is\n one of dataseries members, inner key is in [metric, \'count\', \'identity\'\n \'hit_count\'], value is float.\n '
attribute_values = autovivify(2, float)
if (taxid not in tax_profile.tree.data):
raise KeyError(taxid, 'not found in the tree!!!')
ret_val = (((('\t' * offset) + '<node name="') + tax_profile.tree.data[taxid].name) + '">\n')
offset += 1
if tax_profile.tree.data[taxid].attributes:
if ((metric != 'readcount') and (metric != 'proteincount')):
ret_val += (('\t' * offset) + '<readcount>')
for datapoint in dataseries:
if ((datapoint in tax_profile.tree.data[taxid].attributes) and ('count' in tax_profile.tree.data[taxid].attributes[datapoint])):
ret_val += (('<val>' + format(tax_profile.tree.data[taxid].attributes[datapoint]['count'], '0.0f')) + '</val>')
else:
ret_val += '<val>0</val>'
ret_val += '</readcount>\n'
ret_val += (((('\t' * offset) + '<') + metric) + '>')
for datapoint in dataseries:
if ((datapoint in tax_profile.tree.data[taxid].attributes) and (metric in tax_profile.tree.data[taxid].attributes[datapoint])):
ret_val += (('<val>' + format(tax_profile.tree.data[taxid].attributes[datapoint][metric], '0.6f')) + '</val>')
else:
ret_val += '<val>0.0</val>'
ret_val += (((('</' + metric) + '>\n') + ('\t' * offset)) + '<identity>')
for datapoint in dataseries:
if ((datapoint in tax_profile.tree.data[taxid].attributes) and ('identity' in tax_profile.tree.data[taxid].attributes[datapoint])):
ret_val += (('<val>' + format((tax_profile.tree.data[taxid].attributes[datapoint]['identity'] / tax_profile.tree.data[taxid].attributes[datapoint]['hit_count']), '0.1f')) + '</val>')
else:
ret_val += '<val>0.0</val>'
ret_val += '</identity>\n'
else:
if ((metric != 'readcount') and (metric != 'proteincount')):
ret_val += (('\t' * offset) + '<readcount>')
ret_val += ('<val>0</val>' * len(dataseries))
ret_val += '</readcount>\n'
ret_val += (((('\t' * offset) + '<') + metric) + '>')
ret_val += ('<val>0.0</val>' * len(dataseries))
ret_val += (((('<' + metric) + '>\n') + ('\t' * offset)) + '<identity>')
ret_val += ('<val>0.0</val>' * len(dataseries))
ret_val += '</identity>\n'
if tax_profile.tree.data[taxid].children:
for child_taxid in tax_profile.tree.data[taxid].children:
(child_node, child_values) = get_lca_dataseries_tax_xml(tax_profile, dataseries, child_taxid, offset, metric=metric)
ret_val += child_node
for datapoint in child_values.keys():
for (key, val) in child_values[datapoint].items():
attribute_values[datapoint][key] += val
unidentified_flag = False
for datapoint in dataseries:
if (datapoint in tax_profile.tree.data[taxid].attributes):
if (attribute_values[datapoint]['count'] < tax_profile.tree.data[taxid].attributes[datapoint]['count']):
unidentified_flag = True
break
if unidentified_flag:
if (offset == 2):
ret_val += (('\t' * offset) + '<node name="Unclassified">\n')
else:
ret_val += (((('\t' * offset) + '<node name="Unclassified ') + tax_profile.tree.data[taxid].name) + '">\n')
offset += 1
if ((metric != 'readcount') and (metric != 'proteincount')):
ret_val += (('\t' * offset) + '<readcount>')
for datapoint in dataseries:
if ((datapoint in tax_profile.tree.data[taxid].attributes) and (attribute_values[datapoint]['count'] < tax_profile.tree.data[taxid].attributes[datapoint]['count'])):
ret_val += (('<val>' + format((tax_profile.tree.data[taxid].attributes[datapoint]['count'] - attribute_values[datapoint]['count']), '0.0f')) + '</val>')
else:
ret_val += '<val>0</val>'
ret_val += '</readcount>\n'
ret_val += (((('\t' * offset) + '<') + metric) + '>')
for datapoint in dataseries:
if ((datapoint in tax_profile.tree.data[taxid].attributes) and (attribute_values[datapoint]['count'] < tax_profile.tree.data[taxid].attributes[datapoint]['count'])):
ret_val += (('<val>' + format((tax_profile.tree.data[taxid].attributes[datapoint][metric] - attribute_values[datapoint][metric]), '0.6f')) + '</val>')
else:
ret_val += '<val>0.0</val>'
ret_val += (('</' + metric) + '>\n')
ret_val += (('\t' * offset) + '<identity>')
for datapoint in dataseries:
if ((datapoint in tax_profile.tree.data[taxid].attributes) and ('hit_count' in tax_profile.tree.data[taxid].attributes[datapoint]) and (attribute_values[datapoint]['hit_count'] < tax_profile.tree.data[taxid].attributes[datapoint]['hit_count'])):
ret_val += (('<val>' + format(((tax_profile.tree.data[taxid].attributes[datapoint]['identity'] - attribute_values[datapoint]['identity']) / (tax_profile.tree.data[taxid].attributes[datapoint]['hit_count'] - attribute_values[datapoint]['hit_count'])), '0.1f')) + '</val>')
else:
ret_val += '<val>0.0</val>'
ret_val += '</identity>\n'
offset -= 1
ret_val += (('\t' * offset) + '</node>\n')
offset -= 1
ret_val += (('\t' * offset) + '</node>\n')
attribute_values = autovivify(1)
for datapoint in dataseries:
if (datapoint in tax_profile.tree.data[taxid].attributes):
if (metric in tax_profile.tree.data[taxid].attributes[datapoint]):
attribute_values[datapoint][metric] = tax_profile.tree.data[taxid].attributes[datapoint][metric]
if ('count' in tax_profile.tree.data[taxid].attributes[datapoint]):
attribute_values[datapoint]['count'] = tax_profile.tree.data[taxid].attributes[datapoint]['count']
if ('identity' in tax_profile.tree.data[taxid].attributes[datapoint]):
attribute_values[datapoint]['identity'] = tax_profile.tree.data[taxid].attributes[datapoint]['identity']
if ('hit_count' in tax_profile.tree.data[taxid].attributes[datapoint]):
attribute_values[datapoint]['hit_count'] = tax_profile.tree.data[taxid].attributes[datapoint]['hit_count']
return (ret_val, attribute_values)
|
def get_lca_dataseries_tax_xml(tax_profile, dataseries, taxid, offset, metric='efpkg'):
'Returns XML node for a phylogenetic tree node and all its children.\n Creates additional child node for a fictional "Unclassified..." taxon\n if not all reads of the current node were mapped to children nodes.\n\n Args:\n tax_profile (:obj:TaxonomyProfile): taxonomy profile\n dataseries (list of str): either sample identifiers or function identifiers,\n depending on profile type (functional or taxonomic)\n taxid (str): taxonomy identifier of a node of interest\n offset (int): number of starting tabs\n metric (str): scoring metric (default value \'efpkg\')\n\n Returns:\n ret_val (str): XML node\n attribute_values (defaultdict[str,dict[str,float]]): outer key is\n one of dataseries members, inner key is in [metric, \'count\', \'identity\'\n \'hit_count\'], value is float.\n '
attribute_values = autovivify(2, float)
if (taxid not in tax_profile.tree.data):
raise KeyError(taxid, 'not found in the tree!!!')
ret_val = (((('\t' * offset) + '<node name="') + tax_profile.tree.data[taxid].name) + '">\n')
offset += 1
if tax_profile.tree.data[taxid].attributes:
if ((metric != 'readcount') and (metric != 'proteincount')):
ret_val += (('\t' * offset) + '<readcount>')
for datapoint in dataseries:
if ((datapoint in tax_profile.tree.data[taxid].attributes) and ('count' in tax_profile.tree.data[taxid].attributes[datapoint])):
ret_val += (('<val>' + format(tax_profile.tree.data[taxid].attributes[datapoint]['count'], '0.0f')) + '</val>')
else:
ret_val += '<val>0</val>'
ret_val += '</readcount>\n'
ret_val += (((('\t' * offset) + '<') + metric) + '>')
for datapoint in dataseries:
if ((datapoint in tax_profile.tree.data[taxid].attributes) and (metric in tax_profile.tree.data[taxid].attributes[datapoint])):
ret_val += (('<val>' + format(tax_profile.tree.data[taxid].attributes[datapoint][metric], '0.6f')) + '</val>')
else:
ret_val += '<val>0.0</val>'
ret_val += (((('</' + metric) + '>\n') + ('\t' * offset)) + '<identity>')
for datapoint in dataseries:
if ((datapoint in tax_profile.tree.data[taxid].attributes) and ('identity' in tax_profile.tree.data[taxid].attributes[datapoint])):
ret_val += (('<val>' + format((tax_profile.tree.data[taxid].attributes[datapoint]['identity'] / tax_profile.tree.data[taxid].attributes[datapoint]['hit_count']), '0.1f')) + '</val>')
else:
ret_val += '<val>0.0</val>'
ret_val += '</identity>\n'
else:
if ((metric != 'readcount') and (metric != 'proteincount')):
ret_val += (('\t' * offset) + '<readcount>')
ret_val += ('<val>0</val>' * len(dataseries))
ret_val += '</readcount>\n'
ret_val += (((('\t' * offset) + '<') + metric) + '>')
ret_val += ('<val>0.0</val>' * len(dataseries))
ret_val += (((('<' + metric) + '>\n') + ('\t' * offset)) + '<identity>')
ret_val += ('<val>0.0</val>' * len(dataseries))
ret_val += '</identity>\n'
if tax_profile.tree.data[taxid].children:
for child_taxid in tax_profile.tree.data[taxid].children:
(child_node, child_values) = get_lca_dataseries_tax_xml(tax_profile, dataseries, child_taxid, offset, metric=metric)
ret_val += child_node
for datapoint in child_values.keys():
for (key, val) in child_values[datapoint].items():
attribute_values[datapoint][key] += val
unidentified_flag = False
for datapoint in dataseries:
if (datapoint in tax_profile.tree.data[taxid].attributes):
if (attribute_values[datapoint]['count'] < tax_profile.tree.data[taxid].attributes[datapoint]['count']):
unidentified_flag = True
break
if unidentified_flag:
if (offset == 2):
ret_val += (('\t' * offset) + '<node name="Unclassified">\n')
else:
ret_val += (((('\t' * offset) + '<node name="Unclassified ') + tax_profile.tree.data[taxid].name) + '">\n')
offset += 1
if ((metric != 'readcount') and (metric != 'proteincount')):
ret_val += (('\t' * offset) + '<readcount>')
for datapoint in dataseries:
if ((datapoint in tax_profile.tree.data[taxid].attributes) and (attribute_values[datapoint]['count'] < tax_profile.tree.data[taxid].attributes[datapoint]['count'])):
ret_val += (('<val>' + format((tax_profile.tree.data[taxid].attributes[datapoint]['count'] - attribute_values[datapoint]['count']), '0.0f')) + '</val>')
else:
ret_val += '<val>0</val>'
ret_val += '</readcount>\n'
ret_val += (((('\t' * offset) + '<') + metric) + '>')
for datapoint in dataseries:
if ((datapoint in tax_profile.tree.data[taxid].attributes) and (attribute_values[datapoint]['count'] < tax_profile.tree.data[taxid].attributes[datapoint]['count'])):
ret_val += (('<val>' + format((tax_profile.tree.data[taxid].attributes[datapoint][metric] - attribute_values[datapoint][metric]), '0.6f')) + '</val>')
else:
ret_val += '<val>0.0</val>'
ret_val += (('</' + metric) + '>\n')
ret_val += (('\t' * offset) + '<identity>')
for datapoint in dataseries:
if ((datapoint in tax_profile.tree.data[taxid].attributes) and ('hit_count' in tax_profile.tree.data[taxid].attributes[datapoint]) and (attribute_values[datapoint]['hit_count'] < tax_profile.tree.data[taxid].attributes[datapoint]['hit_count'])):
ret_val += (('<val>' + format(((tax_profile.tree.data[taxid].attributes[datapoint]['identity'] - attribute_values[datapoint]['identity']) / (tax_profile.tree.data[taxid].attributes[datapoint]['hit_count'] - attribute_values[datapoint]['hit_count'])), '0.1f')) + '</val>')
else:
ret_val += '<val>0.0</val>'
ret_val += '</identity>\n'
offset -= 1
ret_val += (('\t' * offset) + '</node>\n')
offset -= 1
ret_val += (('\t' * offset) + '</node>\n')
attribute_values = autovivify(1)
for datapoint in dataseries:
if (datapoint in tax_profile.tree.data[taxid].attributes):
if (metric in tax_profile.tree.data[taxid].attributes[datapoint]):
attribute_values[datapoint][metric] = tax_profile.tree.data[taxid].attributes[datapoint][metric]
if ('count' in tax_profile.tree.data[taxid].attributes[datapoint]):
attribute_values[datapoint]['count'] = tax_profile.tree.data[taxid].attributes[datapoint]['count']
if ('identity' in tax_profile.tree.data[taxid].attributes[datapoint]):
attribute_values[datapoint]['identity'] = tax_profile.tree.data[taxid].attributes[datapoint]['identity']
if ('hit_count' in tax_profile.tree.data[taxid].attributes[datapoint]):
attribute_values[datapoint]['hit_count'] = tax_profile.tree.data[taxid].attributes[datapoint]['hit_count']
return (ret_val, attribute_values)<|docstring|>Returns XML node for a phylogenetic tree node and all its children.
Creates additional child node for a fictional "Unclassified..." taxon
if not all reads of the current node were mapped to children nodes.
Args:
tax_profile (:obj:TaxonomyProfile): taxonomy profile
dataseries (list of str): either sample identifiers or function identifiers,
depending on profile type (functional or taxonomic)
taxid (str): taxonomy identifier of a node of interest
offset (int): number of starting tabs
metric (str): scoring metric (default value 'efpkg')
Returns:
ret_val (str): XML node
attribute_values (defaultdict[str,dict[str,float]]): outer key is
one of dataseries members, inner key is in [metric, 'count', 'identity'
'hit_count'], value is float.<|endoftext|>
|
ca03ab9a80b035626dbe3571ee034261fc61001de4c8ae4eeec55fe18f52402c
|
def get_dataseries_tax_xml(tax_profile, dataseries, taxid, offset, metric='efpkg'):
"Returns XML node for a phylogenetic tree node and all its children.\n\n Args:\n tax_profile (:obj:TaxonomyProfile): taxonomy profile\n dataseries (list of str): either sample identifiers or function identifiers,\n depending on profile type (functional or taxonomic)\n taxid (str): taxonomy identifier of a node of interest\n offset (int): number of starting tabs\n metric (str): scoring metric (default value 'efpkg')\n\n Returns:\n ret_val (str): XML node\n "
if (taxid not in tax_profile.tree.data):
raise KeyError(taxid, 'not found in the tree!!!')
ret_val = (((('\t' * offset) + '<node name="') + tax_profile.tree.data[taxid].name) + '">\n')
offset += 1
if tax_profile.tree.data[taxid].attributes:
if ((metric != 'readcount') and (metric != 'proteincount')):
ret_val += (('\t' * offset) + '<readcount>')
for datapoint in dataseries:
if (datapoint in tax_profile.tree.data[taxid].attributes):
ret_val += (('<val>' + format(tax_profile.tree.data[taxid].attributes[datapoint]['count'], '0.0f')) + '</val>')
else:
ret_val += '<val>0</val>'
ret_val += '</readcount>\n'
ret_val += (((('\t' * offset) + '<') + metric) + '>')
for datapoint in dataseries:
if (datapoint in tax_profile.tree.data[taxid].attributes):
ret_val += (('<val>' + format(tax_profile.tree.data[taxid].attributes[datapoint][metric], '0.5f')) + '</val>')
else:
ret_val += '<val>0.0</val>'
ret_val += (((('</' + metric) + '>\n') + ('\t' * offset)) + '<identity>')
for datapoint in dataseries:
if (datapoint in tax_profile.tree.data[taxid].attributes):
ret_val += (('<val>' + format((tax_profile.tree.data[taxid].attributes[datapoint]['identity'] / tax_profile.tree.data[taxid].attributes[datapoint]['hit_count']), '0.1f')) + '</val>')
else:
ret_val += '<val>0.0</val>'
ret_val += '</identity>\n'
else:
if ((metric != 'readcount') and (metric != 'proteincount')):
ret_val += (('\t' * offset) + '<readcount>')
ret_val += ('<val>0</val>' * len(dataseries))
ret_val += '</readcount>\n'
ret_val += (((('\t' * offset) + '<') + metric) + '>')
ret_val += ('<val>0.0</val>' * len(dataseries))
ret_val += (((('<' + metric) + '>\n') + ('\t' * offset)) + '<identity>')
ret_val += ('<val>0.0</val>' * len(dataseries))
ret_val += '</identity>\n'
if tax_profile.tree.data[taxid].children:
for child_taxid in tax_profile.tree.data[taxid].children:
ret_val += get_dataseries_tax_xml(tax_profile, dataseries, child_taxid, offset, metric=metric)
offset -= 1
ret_val += (('\t' * offset) + '</node>\n')
return ret_val
|
Returns XML node for a phylogenetic tree node and all its children.
Args:
tax_profile (:obj:TaxonomyProfile): taxonomy profile
dataseries (list of str): either sample identifiers or function identifiers,
depending on profile type (functional or taxonomic)
taxid (str): taxonomy identifier of a node of interest
offset (int): number of starting tabs
metric (str): scoring metric (default value 'efpkg')
Returns:
ret_val (str): XML node
|
lib/fama/output/krona_xml_writer.py
|
get_dataseries_tax_xml
|
aekazakov/FamaProfiling
| 0 |
python
|
def get_dataseries_tax_xml(tax_profile, dataseries, taxid, offset, metric='efpkg'):
"Returns XML node for a phylogenetic tree node and all its children.\n\n Args:\n tax_profile (:obj:TaxonomyProfile): taxonomy profile\n dataseries (list of str): either sample identifiers or function identifiers,\n depending on profile type (functional or taxonomic)\n taxid (str): taxonomy identifier of a node of interest\n offset (int): number of starting tabs\n metric (str): scoring metric (default value 'efpkg')\n\n Returns:\n ret_val (str): XML node\n "
if (taxid not in tax_profile.tree.data):
raise KeyError(taxid, 'not found in the tree!!!')
ret_val = (((('\t' * offset) + '<node name="') + tax_profile.tree.data[taxid].name) + '">\n')
offset += 1
if tax_profile.tree.data[taxid].attributes:
if ((metric != 'readcount') and (metric != 'proteincount')):
ret_val += (('\t' * offset) + '<readcount>')
for datapoint in dataseries:
if (datapoint in tax_profile.tree.data[taxid].attributes):
ret_val += (('<val>' + format(tax_profile.tree.data[taxid].attributes[datapoint]['count'], '0.0f')) + '</val>')
else:
ret_val += '<val>0</val>'
ret_val += '</readcount>\n'
ret_val += (((('\t' * offset) + '<') + metric) + '>')
for datapoint in dataseries:
if (datapoint in tax_profile.tree.data[taxid].attributes):
ret_val += (('<val>' + format(tax_profile.tree.data[taxid].attributes[datapoint][metric], '0.5f')) + '</val>')
else:
ret_val += '<val>0.0</val>'
ret_val += (((('</' + metric) + '>\n') + ('\t' * offset)) + '<identity>')
for datapoint in dataseries:
if (datapoint in tax_profile.tree.data[taxid].attributes):
ret_val += (('<val>' + format((tax_profile.tree.data[taxid].attributes[datapoint]['identity'] / tax_profile.tree.data[taxid].attributes[datapoint]['hit_count']), '0.1f')) + '</val>')
else:
ret_val += '<val>0.0</val>'
ret_val += '</identity>\n'
else:
if ((metric != 'readcount') and (metric != 'proteincount')):
ret_val += (('\t' * offset) + '<readcount>')
ret_val += ('<val>0</val>' * len(dataseries))
ret_val += '</readcount>\n'
ret_val += (((('\t' * offset) + '<') + metric) + '>')
ret_val += ('<val>0.0</val>' * len(dataseries))
ret_val += (((('<' + metric) + '>\n') + ('\t' * offset)) + '<identity>')
ret_val += ('<val>0.0</val>' * len(dataseries))
ret_val += '</identity>\n'
if tax_profile.tree.data[taxid].children:
for child_taxid in tax_profile.tree.data[taxid].children:
ret_val += get_dataseries_tax_xml(tax_profile, dataseries, child_taxid, offset, metric=metric)
offset -= 1
ret_val += (('\t' * offset) + '</node>\n')
return ret_val
|
def get_dataseries_tax_xml(tax_profile, dataseries, taxid, offset, metric='efpkg'):
"Returns XML node for a phylogenetic tree node and all its children.\n\n Args:\n tax_profile (:obj:TaxonomyProfile): taxonomy profile\n dataseries (list of str): either sample identifiers or function identifiers,\n depending on profile type (functional or taxonomic)\n taxid (str): taxonomy identifier of a node of interest\n offset (int): number of starting tabs\n metric (str): scoring metric (default value 'efpkg')\n\n Returns:\n ret_val (str): XML node\n "
if (taxid not in tax_profile.tree.data):
raise KeyError(taxid, 'not found in the tree!!!')
ret_val = (((('\t' * offset) + '<node name="') + tax_profile.tree.data[taxid].name) + '">\n')
offset += 1
if tax_profile.tree.data[taxid].attributes:
if ((metric != 'readcount') and (metric != 'proteincount')):
ret_val += (('\t' * offset) + '<readcount>')
for datapoint in dataseries:
if (datapoint in tax_profile.tree.data[taxid].attributes):
ret_val += (('<val>' + format(tax_profile.tree.data[taxid].attributes[datapoint]['count'], '0.0f')) + '</val>')
else:
ret_val += '<val>0</val>'
ret_val += '</readcount>\n'
ret_val += (((('\t' * offset) + '<') + metric) + '>')
for datapoint in dataseries:
if (datapoint in tax_profile.tree.data[taxid].attributes):
ret_val += (('<val>' + format(tax_profile.tree.data[taxid].attributes[datapoint][metric], '0.5f')) + '</val>')
else:
ret_val += '<val>0.0</val>'
ret_val += (((('</' + metric) + '>\n') + ('\t' * offset)) + '<identity>')
for datapoint in dataseries:
if (datapoint in tax_profile.tree.data[taxid].attributes):
ret_val += (('<val>' + format((tax_profile.tree.data[taxid].attributes[datapoint]['identity'] / tax_profile.tree.data[taxid].attributes[datapoint]['hit_count']), '0.1f')) + '</val>')
else:
ret_val += '<val>0.0</val>'
ret_val += '</identity>\n'
else:
if ((metric != 'readcount') and (metric != 'proteincount')):
ret_val += (('\t' * offset) + '<readcount>')
ret_val += ('<val>0</val>' * len(dataseries))
ret_val += '</readcount>\n'
ret_val += (((('\t' * offset) + '<') + metric) + '>')
ret_val += ('<val>0.0</val>' * len(dataseries))
ret_val += (((('<' + metric) + '>\n') + ('\t' * offset)) + '<identity>')
ret_val += ('<val>0.0</val>' * len(dataseries))
ret_val += '</identity>\n'
if tax_profile.tree.data[taxid].children:
for child_taxid in tax_profile.tree.data[taxid].children:
ret_val += get_dataseries_tax_xml(tax_profile, dataseries, child_taxid, offset, metric=metric)
offset -= 1
ret_val += (('\t' * offset) + '</node>\n')
return ret_val<|docstring|>Returns XML node for a phylogenetic tree node and all its children.
Args:
tax_profile (:obj:TaxonomyProfile): taxonomy profile
dataseries (list of str): either sample identifiers or function identifiers,
depending on profile type (functional or taxonomic)
taxid (str): taxonomy identifier of a node of interest
offset (int): number of starting tabs
metric (str): scoring metric (default value 'efpkg')
Returns:
ret_val (str): XML node<|endoftext|>
|
34579e30607e9fe71a00c4876b6d84f57522dbf755028043c4d3fe14e9a0be26
|
def make_function_taxonomy_chart(tax_profile, function_list, outfile, krona_path, metric='efpkg'):
'Writes XML file for taxonomy chart of multiple functions in one sample\n and generates Krona plot from it\n\n Args:\n tax_profile (:obj:TaxonomyProfile): taxonomy profile object\n function_list (list of str): function identifiers\n outfile (str): path for XML output\n krona_path (str): Krona Tools command\n metric (str): scoring metric (efpkg by default)\n '
with open(outfile, 'w') as out:
out.write('<krona key="false">\n')
out.write((('\t<attributes magnitude="' + metric) + '">\n'))
if (metric == 'proteincount'):
out.write((('\t\t<attribute display="Protein count">' + metric) + '</attribute>\n'))
else:
out.write('\t\t<attribute display="Read count">readcount</attribute>\n')
if ((metric != 'readcount') and (metric != 'proteincount')):
out.write((((('\t\t<attribute display="Score:' + metric) + '">') + metric) + '</attribute>\n'))
out.write('\t\t<attribute display="Best hit identity %" mono="true">identity</attribute>\n')
out.write('\t</attributes>\n')
out.write(('\t<color attribute="identity" valueStart="50" valueEnd="100" hueStart="0" ' + 'hueEnd="240" default="true"></color>\n'))
out.write('\t<datasets>\n')
for function in function_list:
out.write((('\t\t<dataset>' + function) + '</dataset>\n'))
out.write('\t</datasets>\n')
offset = 1
out.write(get_dataseries_tax_xml(tax_profile, function_list, ROOT_TAXONOMY_ID, offset, metric=metric))
out.write('</krona>')
html_file = (outfile + '.html')
krona_cmd = [krona_path, '-o', html_file, outfile]
run_external_program(krona_cmd)
|
Writes XML file for taxonomy chart of multiple functions in one sample
and generates Krona plot from it
Args:
tax_profile (:obj:TaxonomyProfile): taxonomy profile object
function_list (list of str): function identifiers
outfile (str): path for XML output
krona_path (str): Krona Tools command
metric (str): scoring metric (efpkg by default)
|
lib/fama/output/krona_xml_writer.py
|
make_function_taxonomy_chart
|
aekazakov/FamaProfiling
| 0 |
python
|
def make_function_taxonomy_chart(tax_profile, function_list, outfile, krona_path, metric='efpkg'):
'Writes XML file for taxonomy chart of multiple functions in one sample\n and generates Krona plot from it\n\n Args:\n tax_profile (:obj:TaxonomyProfile): taxonomy profile object\n function_list (list of str): function identifiers\n outfile (str): path for XML output\n krona_path (str): Krona Tools command\n metric (str): scoring metric (efpkg by default)\n '
with open(outfile, 'w') as out:
out.write('<krona key="false">\n')
out.write((('\t<attributes magnitude="' + metric) + '">\n'))
if (metric == 'proteincount'):
out.write((('\t\t<attribute display="Protein count">' + metric) + '</attribute>\n'))
else:
out.write('\t\t<attribute display="Read count">readcount</attribute>\n')
if ((metric != 'readcount') and (metric != 'proteincount')):
out.write((((('\t\t<attribute display="Score:' + metric) + '">') + metric) + '</attribute>\n'))
out.write('\t\t<attribute display="Best hit identity %" mono="true">identity</attribute>\n')
out.write('\t</attributes>\n')
out.write(('\t<color attribute="identity" valueStart="50" valueEnd="100" hueStart="0" ' + 'hueEnd="240" default="true"></color>\n'))
out.write('\t<datasets>\n')
for function in function_list:
out.write((('\t\t<dataset>' + function) + '</dataset>\n'))
out.write('\t</datasets>\n')
offset = 1
out.write(get_dataseries_tax_xml(tax_profile, function_list, ROOT_TAXONOMY_ID, offset, metric=metric))
out.write('</krona>')
html_file = (outfile + '.html')
krona_cmd = [krona_path, '-o', html_file, outfile]
run_external_program(krona_cmd)
|
def make_function_taxonomy_chart(tax_profile, function_list, outfile, krona_path, metric='efpkg'):
'Writes XML file for taxonomy chart of multiple functions in one sample\n and generates Krona plot from it\n\n Args:\n tax_profile (:obj:TaxonomyProfile): taxonomy profile object\n function_list (list of str): function identifiers\n outfile (str): path for XML output\n krona_path (str): Krona Tools command\n metric (str): scoring metric (efpkg by default)\n '
with open(outfile, 'w') as out:
out.write('<krona key="false">\n')
out.write((('\t<attributes magnitude="' + metric) + '">\n'))
if (metric == 'proteincount'):
out.write((('\t\t<attribute display="Protein count">' + metric) + '</attribute>\n'))
else:
out.write('\t\t<attribute display="Read count">readcount</attribute>\n')
if ((metric != 'readcount') and (metric != 'proteincount')):
out.write((((('\t\t<attribute display="Score:' + metric) + '">') + metric) + '</attribute>\n'))
out.write('\t\t<attribute display="Best hit identity %" mono="true">identity</attribute>\n')
out.write('\t</attributes>\n')
out.write(('\t<color attribute="identity" valueStart="50" valueEnd="100" hueStart="0" ' + 'hueEnd="240" default="true"></color>\n'))
out.write('\t<datasets>\n')
for function in function_list:
out.write((('\t\t<dataset>' + function) + '</dataset>\n'))
out.write('\t</datasets>\n')
offset = 1
out.write(get_dataseries_tax_xml(tax_profile, function_list, ROOT_TAXONOMY_ID, offset, metric=metric))
out.write('</krona>')
html_file = (outfile + '.html')
krona_cmd = [krona_path, '-o', html_file, outfile]
run_external_program(krona_cmd)<|docstring|>Writes XML file for taxonomy chart of multiple functions in one sample
and generates Krona plot from it
Args:
tax_profile (:obj:TaxonomyProfile): taxonomy profile object
function_list (list of str): function identifiers
outfile (str): path for XML output
krona_path (str): Krona Tools command
metric (str): scoring metric (efpkg by default)<|endoftext|>
|
b7cb8a295ac51753882354353d5748a28324e115c42bfceb562ba401a3e825ff
|
def get_genes_xml(gene_data, gene_ids, dataseries, offset, metric):
"Returns XML nodes for all predicted gene from one taxon.\n\n Args:\n gene_data (defaultdict[str,defaultdict[str,dict[str,float]]]): outer key is\n gene identifier, middle key is function identifier, inner key is in\n [metric, 'count', 'identity', 'coverage', 'Length', 'Completeness'],\n value is float.\n gene_ids (list of str): gene identifiers\n dataseries (list of str): either sample identifiers or function identifiers,\n depending on profile type (functional or taxonomic)\n offset (int): number of starting tabs\n metric (str): scoring metric\n\n Returns:\n ret_val (str): XML node\n attribute_values (defaultdict[str,dict[str,float]]): outer key is\n one of dataseries members, inner key is in [metric, 'count', 'identity'\n 'hit_count'], value is float.\n "
ret_val = ''
for gene_id in gene_ids:
ret_val += (((('\t' * offset) + '<node name="') + gene_id) + '">\n')
offset += 1
if (metric != 'readcount'):
ret_val += (('\t' * offset) + '<readcount>')
for datapoint in dataseries:
if (datapoint in gene_data[gene_id]):
ret_val += (('<val>' + gene_data[gene_id][datapoint]['count']) + '</val>')
else:
ret_val += '<val>0</val>'
ret_val += '</readcount>\n'
ret_val += (((('\t' * offset) + '<') + metric) + '>')
for datapoint in dataseries:
if (datapoint in gene_data[gene_id]):
ret_val += (('<val>' + gene_data[gene_id][datapoint][metric]) + '</val>')
else:
ret_val += '<val>0</val>'
ret_val += (('</' + metric) + '>\n')
ret_val += (('\t' * offset) + '<coverage>')
for datapoint in dataseries:
if (datapoint in gene_data[gene_id]):
ret_val += (('<val>' + gene_data[gene_id][datapoint]['coverage']) + '</val>')
else:
ret_val += '<val>0</val>'
ret_val += '</coverage>\n'
ret_val += (('\t' * offset) + '<identity>')
for datapoint in dataseries:
if (datapoint in gene_data[gene_id]):
ret_val += (('<val>' + gene_data[gene_id][datapoint]['identity']) + '</val>')
else:
ret_val += '<val>0</val>'
ret_val += '</identity>\n'
ret_val += (('\t' * offset) + '<Length>')
for datapoint in dataseries:
if (datapoint in gene_data[gene_id]):
ret_val += (('<val>' + gene_data[gene_id][datapoint]['Length']) + '</val>')
else:
ret_val += '<val>0</val>'
ret_val += '</Length>\n'
ret_val += (('\t' * offset) + '<Completeness>')
for datapoint in dataseries:
if (datapoint in gene_data[gene_id]):
ret_val += (('<val>' + gene_data[gene_id][datapoint]['Completeness']) + '</val>')
else:
ret_val += '<val>0</val>'
ret_val += '</Completeness>\n'
ret_val += (('\t' * offset) + '<best_hit>')
for datapoint in dataseries:
if ((datapoint in gene_data[gene_id]) and ('Best hit' in gene_data[gene_id][datapoint])):
ret_val += (((('<val href="' + gene_data[gene_id][datapoint]['Best hit']) + '">') + gene_data[gene_id][datapoint]['Best hit']) + '</val>')
else:
ret_val += '<val></val>'
ret_val += '</best_hit>\n'
offset -= 1
ret_val += (('\t' * offset) + '</node>\n')
return ret_val
|
Returns XML nodes for all predicted gene from one taxon.
Args:
gene_data (defaultdict[str,defaultdict[str,dict[str,float]]]): outer key is
gene identifier, middle key is function identifier, inner key is in
[metric, 'count', 'identity', 'coverage', 'Length', 'Completeness'],
value is float.
gene_ids (list of str): gene identifiers
dataseries (list of str): either sample identifiers or function identifiers,
depending on profile type (functional or taxonomic)
offset (int): number of starting tabs
metric (str): scoring metric
Returns:
ret_val (str): XML node
attribute_values (defaultdict[str,dict[str,float]]): outer key is
one of dataseries members, inner key is in [metric, 'count', 'identity'
'hit_count'], value is float.
|
lib/fama/output/krona_xml_writer.py
|
get_genes_xml
|
aekazakov/FamaProfiling
| 0 |
python
|
def get_genes_xml(gene_data, gene_ids, dataseries, offset, metric):
"Returns XML nodes for all predicted gene from one taxon.\n\n Args:\n gene_data (defaultdict[str,defaultdict[str,dict[str,float]]]): outer key is\n gene identifier, middle key is function identifier, inner key is in\n [metric, 'count', 'identity', 'coverage', 'Length', 'Completeness'],\n value is float.\n gene_ids (list of str): gene identifiers\n dataseries (list of str): either sample identifiers or function identifiers,\n depending on profile type (functional or taxonomic)\n offset (int): number of starting tabs\n metric (str): scoring metric\n\n Returns:\n ret_val (str): XML node\n attribute_values (defaultdict[str,dict[str,float]]): outer key is\n one of dataseries members, inner key is in [metric, 'count', 'identity'\n 'hit_count'], value is float.\n "
ret_val =
for gene_id in gene_ids:
ret_val += (((('\t' * offset) + '<node name="') + gene_id) + '">\n')
offset += 1
if (metric != 'readcount'):
ret_val += (('\t' * offset) + '<readcount>')
for datapoint in dataseries:
if (datapoint in gene_data[gene_id]):
ret_val += (('<val>' + gene_data[gene_id][datapoint]['count']) + '</val>')
else:
ret_val += '<val>0</val>'
ret_val += '</readcount>\n'
ret_val += (((('\t' * offset) + '<') + metric) + '>')
for datapoint in dataseries:
if (datapoint in gene_data[gene_id]):
ret_val += (('<val>' + gene_data[gene_id][datapoint][metric]) + '</val>')
else:
ret_val += '<val>0</val>'
ret_val += (('</' + metric) + '>\n')
ret_val += (('\t' * offset) + '<coverage>')
for datapoint in dataseries:
if (datapoint in gene_data[gene_id]):
ret_val += (('<val>' + gene_data[gene_id][datapoint]['coverage']) + '</val>')
else:
ret_val += '<val>0</val>'
ret_val += '</coverage>\n'
ret_val += (('\t' * offset) + '<identity>')
for datapoint in dataseries:
if (datapoint in gene_data[gene_id]):
ret_val += (('<val>' + gene_data[gene_id][datapoint]['identity']) + '</val>')
else:
ret_val += '<val>0</val>'
ret_val += '</identity>\n'
ret_val += (('\t' * offset) + '<Length>')
for datapoint in dataseries:
if (datapoint in gene_data[gene_id]):
ret_val += (('<val>' + gene_data[gene_id][datapoint]['Length']) + '</val>')
else:
ret_val += '<val>0</val>'
ret_val += '</Length>\n'
ret_val += (('\t' * offset) + '<Completeness>')
for datapoint in dataseries:
if (datapoint in gene_data[gene_id]):
ret_val += (('<val>' + gene_data[gene_id][datapoint]['Completeness']) + '</val>')
else:
ret_val += '<val>0</val>'
ret_val += '</Completeness>\n'
ret_val += (('\t' * offset) + '<best_hit>')
for datapoint in dataseries:
if ((datapoint in gene_data[gene_id]) and ('Best hit' in gene_data[gene_id][datapoint])):
ret_val += (((('<val href="' + gene_data[gene_id][datapoint]['Best hit']) + '">') + gene_data[gene_id][datapoint]['Best hit']) + '</val>')
else:
ret_val += '<val></val>'
ret_val += '</best_hit>\n'
offset -= 1
ret_val += (('\t' * offset) + '</node>\n')
return ret_val
|
def get_genes_xml(gene_data, gene_ids, dataseries, offset, metric):
"Returns XML nodes for all predicted gene from one taxon.\n\n Args:\n gene_data (defaultdict[str,defaultdict[str,dict[str,float]]]): outer key is\n gene identifier, middle key is function identifier, inner key is in\n [metric, 'count', 'identity', 'coverage', 'Length', 'Completeness'],\n value is float.\n gene_ids (list of str): gene identifiers\n dataseries (list of str): either sample identifiers or function identifiers,\n depending on profile type (functional or taxonomic)\n offset (int): number of starting tabs\n metric (str): scoring metric\n\n Returns:\n ret_val (str): XML node\n attribute_values (defaultdict[str,dict[str,float]]): outer key is\n one of dataseries members, inner key is in [metric, 'count', 'identity'\n 'hit_count'], value is float.\n "
ret_val =
for gene_id in gene_ids:
ret_val += (((('\t' * offset) + '<node name="') + gene_id) + '">\n')
offset += 1
if (metric != 'readcount'):
ret_val += (('\t' * offset) + '<readcount>')
for datapoint in dataseries:
if (datapoint in gene_data[gene_id]):
ret_val += (('<val>' + gene_data[gene_id][datapoint]['count']) + '</val>')
else:
ret_val += '<val>0</val>'
ret_val += '</readcount>\n'
ret_val += (((('\t' * offset) + '<') + metric) + '>')
for datapoint in dataseries:
if (datapoint in gene_data[gene_id]):
ret_val += (('<val>' + gene_data[gene_id][datapoint][metric]) + '</val>')
else:
ret_val += '<val>0</val>'
ret_val += (('</' + metric) + '>\n')
ret_val += (('\t' * offset) + '<coverage>')
for datapoint in dataseries:
if (datapoint in gene_data[gene_id]):
ret_val += (('<val>' + gene_data[gene_id][datapoint]['coverage']) + '</val>')
else:
ret_val += '<val>0</val>'
ret_val += '</coverage>\n'
ret_val += (('\t' * offset) + '<identity>')
for datapoint in dataseries:
if (datapoint in gene_data[gene_id]):
ret_val += (('<val>' + gene_data[gene_id][datapoint]['identity']) + '</val>')
else:
ret_val += '<val>0</val>'
ret_val += '</identity>\n'
ret_val += (('\t' * offset) + '<Length>')
for datapoint in dataseries:
if (datapoint in gene_data[gene_id]):
ret_val += (('<val>' + gene_data[gene_id][datapoint]['Length']) + '</val>')
else:
ret_val += '<val>0</val>'
ret_val += '</Length>\n'
ret_val += (('\t' * offset) + '<Completeness>')
for datapoint in dataseries:
if (datapoint in gene_data[gene_id]):
ret_val += (('<val>' + gene_data[gene_id][datapoint]['Completeness']) + '</val>')
else:
ret_val += '<val>0</val>'
ret_val += '</Completeness>\n'
ret_val += (('\t' * offset) + '<best_hit>')
for datapoint in dataseries:
if ((datapoint in gene_data[gene_id]) and ('Best hit' in gene_data[gene_id][datapoint])):
ret_val += (((('<val href="' + gene_data[gene_id][datapoint]['Best hit']) + '">') + gene_data[gene_id][datapoint]['Best hit']) + '</val>')
else:
ret_val += '<val></val>'
ret_val += '</best_hit>\n'
offset -= 1
ret_val += (('\t' * offset) + '</node>\n')
return ret_val<|docstring|>Returns XML nodes for all predicted gene from one taxon.
Args:
gene_data (defaultdict[str,defaultdict[str,dict[str,float]]]): outer key is
gene identifier, middle key is function identifier, inner key is in
[metric, 'count', 'identity', 'coverage', 'Length', 'Completeness'],
value is float.
gene_ids (list of str): gene identifiers
dataseries (list of str): either sample identifiers or function identifiers,
depending on profile type (functional or taxonomic)
offset (int): number of starting tabs
metric (str): scoring metric
Returns:
ret_val (str): XML node
attribute_values (defaultdict[str,dict[str,float]]): outer key is
one of dataseries members, inner key is in [metric, 'count', 'identity'
'hit_count'], value is float.<|endoftext|>
|
435a95c0d449a031123c4679314077239c65b578860e7122b4397d50a7895de9
|
def get_assembly_tax_xml(tax_profile, genes, dataseries, taxid, offset, metric='efpkg'):
"Returns XML node for assembly phylogenetic tree node and all its children.\n\n Args:\n tax_profile (:obj:TaxonomyProfile): taxonomy profile\n genes (defaultdict[str,defaultdict[str,dict[str,float]]]): outer key is\n gene identifier, middle key is function identifier, inner key is in\n [metric, 'count', 'identity', 'coverage', 'Length', 'Completeness'],\n value is float (genes[gene_id][function_id][parameter_name] = parameter_value).\n dataseries (list of str): function identifiers\n taxid (str): taxonomy identifier of a node of interest\n offset (int): number of starting tabs\n metric (str): scoring metric (default value 'efpkg')\n\n Returns:\n ret_val (str): XML node\n "
if (taxid not in tax_profile.tree.data):
raise KeyError(taxid, 'not found in the tree!!!')
ret_val = (((((('\t' * offset) + '<node name="') + taxid) + ':') + tax_profile.tree.data[taxid].name) + '">\n')
offset += 1
if tax_profile.tree.data[taxid].attributes:
if (metric != 'readcount'):
ret_val += (('\t' * offset) + '<readcount>')
for datapoint in dataseries:
if (datapoint in tax_profile.tree.data[taxid].attributes):
ret_val += (('<val>' + format(tax_profile.tree.data[taxid].attributes[datapoint]['count'], '0.0f')) + '</val>')
else:
ret_val += '<val>0</val>'
ret_val += '</readcount>\n'
ret_val += (((('\t' * offset) + '<') + metric) + '>')
for datapoint in dataseries:
if (datapoint in tax_profile.tree.data[taxid].attributes):
ret_val += (('<val>' + format(tax_profile.tree.data[taxid].attributes[datapoint][metric], '0.7f')) + '</val>')
else:
ret_val += '<val>0.0</val>'
ret_val += (((('</' + metric) + '>\n') + ('\t' * offset)) + '<identity>')
for datapoint in dataseries:
if ((datapoint in tax_profile.tree.data[taxid].attributes) and (tax_profile.tree.data[taxid].attributes[datapoint]['hit_count'] > 0)):
ret_val += (('<val>' + format((tax_profile.tree.data[taxid].attributes[datapoint]['identity'] / tax_profile.tree.data[taxid].attributes[datapoint]['hit_count']), '0.1f')) + '</val>')
else:
ret_val += '<val>0.0</val>'
ret_val += '</identity>\n'
gene_ids = set()
for datapoint in tax_profile.tree.data[taxid].attributes:
if ('genes' in tax_profile.tree.data[taxid].attributes[datapoint]):
for gene_id in tax_profile.tree.data[taxid].attributes[datapoint]['genes'].split(' '):
gene_ids.add(gene_id)
ret_val += get_genes_xml(genes, sorted(gene_ids), dataseries, offset, metric)
else:
if (metric != 'readcount'):
ret_val += (('\t' * offset) + '<readcount>')
ret_val += ('<val>0</val>' * len(dataseries))
ret_val += '</readcount>\n'
ret_val += (((('\t' * offset) + '<') + metric) + '>')
ret_val += ('<val>0.0</val>' * len(dataseries))
ret_val += (((('</' + metric) + '>\n') + ('\t' * offset)) + '<identity>')
ret_val += ('<val>0.0%</val>' * len(dataseries))
ret_val += '</identity>\n'
if tax_profile.tree.data[taxid].children:
for child_taxid in tax_profile.tree.data[taxid].children:
ret_val += get_assembly_tax_xml(tax_profile, genes, dataseries, child_taxid, offset, metric)
offset -= 1
ret_val += (('\t' * offset) + '</node>\n')
return ret_val
|
Returns XML node for assembly phylogenetic tree node and all its children.
Args:
tax_profile (:obj:TaxonomyProfile): taxonomy profile
genes (defaultdict[str,defaultdict[str,dict[str,float]]]): outer key is
gene identifier, middle key is function identifier, inner key is in
[metric, 'count', 'identity', 'coverage', 'Length', 'Completeness'],
value is float (genes[gene_id][function_id][parameter_name] = parameter_value).
dataseries (list of str): function identifiers
taxid (str): taxonomy identifier of a node of interest
offset (int): number of starting tabs
metric (str): scoring metric (default value 'efpkg')
Returns:
ret_val (str): XML node
|
lib/fama/output/krona_xml_writer.py
|
get_assembly_tax_xml
|
aekazakov/FamaProfiling
| 0 |
python
|
def get_assembly_tax_xml(tax_profile, genes, dataseries, taxid, offset, metric='efpkg'):
"Returns XML node for assembly phylogenetic tree node and all its children.\n\n Args:\n tax_profile (:obj:TaxonomyProfile): taxonomy profile\n genes (defaultdict[str,defaultdict[str,dict[str,float]]]): outer key is\n gene identifier, middle key is function identifier, inner key is in\n [metric, 'count', 'identity', 'coverage', 'Length', 'Completeness'],\n value is float (genes[gene_id][function_id][parameter_name] = parameter_value).\n dataseries (list of str): function identifiers\n taxid (str): taxonomy identifier of a node of interest\n offset (int): number of starting tabs\n metric (str): scoring metric (default value 'efpkg')\n\n Returns:\n ret_val (str): XML node\n "
if (taxid not in tax_profile.tree.data):
raise KeyError(taxid, 'not found in the tree!!!')
ret_val = (((((('\t' * offset) + '<node name="') + taxid) + ':') + tax_profile.tree.data[taxid].name) + '">\n')
offset += 1
if tax_profile.tree.data[taxid].attributes:
if (metric != 'readcount'):
ret_val += (('\t' * offset) + '<readcount>')
for datapoint in dataseries:
if (datapoint in tax_profile.tree.data[taxid].attributes):
ret_val += (('<val>' + format(tax_profile.tree.data[taxid].attributes[datapoint]['count'], '0.0f')) + '</val>')
else:
ret_val += '<val>0</val>'
ret_val += '</readcount>\n'
ret_val += (((('\t' * offset) + '<') + metric) + '>')
for datapoint in dataseries:
if (datapoint in tax_profile.tree.data[taxid].attributes):
ret_val += (('<val>' + format(tax_profile.tree.data[taxid].attributes[datapoint][metric], '0.7f')) + '</val>')
else:
ret_val += '<val>0.0</val>'
ret_val += (((('</' + metric) + '>\n') + ('\t' * offset)) + '<identity>')
for datapoint in dataseries:
if ((datapoint in tax_profile.tree.data[taxid].attributes) and (tax_profile.tree.data[taxid].attributes[datapoint]['hit_count'] > 0)):
ret_val += (('<val>' + format((tax_profile.tree.data[taxid].attributes[datapoint]['identity'] / tax_profile.tree.data[taxid].attributes[datapoint]['hit_count']), '0.1f')) + '</val>')
else:
ret_val += '<val>0.0</val>'
ret_val += '</identity>\n'
gene_ids = set()
for datapoint in tax_profile.tree.data[taxid].attributes:
if ('genes' in tax_profile.tree.data[taxid].attributes[datapoint]):
for gene_id in tax_profile.tree.data[taxid].attributes[datapoint]['genes'].split(' '):
gene_ids.add(gene_id)
ret_val += get_genes_xml(genes, sorted(gene_ids), dataseries, offset, metric)
else:
if (metric != 'readcount'):
ret_val += (('\t' * offset) + '<readcount>')
ret_val += ('<val>0</val>' * len(dataseries))
ret_val += '</readcount>\n'
ret_val += (((('\t' * offset) + '<') + metric) + '>')
ret_val += ('<val>0.0</val>' * len(dataseries))
ret_val += (((('</' + metric) + '>\n') + ('\t' * offset)) + '<identity>')
ret_val += ('<val>0.0%</val>' * len(dataseries))
ret_val += '</identity>\n'
if tax_profile.tree.data[taxid].children:
for child_taxid in tax_profile.tree.data[taxid].children:
ret_val += get_assembly_tax_xml(tax_profile, genes, dataseries, child_taxid, offset, metric)
offset -= 1
ret_val += (('\t' * offset) + '</node>\n')
return ret_val
|
def get_assembly_tax_xml(tax_profile, genes, dataseries, taxid, offset, metric='efpkg'):
"Returns XML node for assembly phylogenetic tree node and all its children.\n\n Args:\n tax_profile (:obj:TaxonomyProfile): taxonomy profile\n genes (defaultdict[str,defaultdict[str,dict[str,float]]]): outer key is\n gene identifier, middle key is function identifier, inner key is in\n [metric, 'count', 'identity', 'coverage', 'Length', 'Completeness'],\n value is float (genes[gene_id][function_id][parameter_name] = parameter_value).\n dataseries (list of str): function identifiers\n taxid (str): taxonomy identifier of a node of interest\n offset (int): number of starting tabs\n metric (str): scoring metric (default value 'efpkg')\n\n Returns:\n ret_val (str): XML node\n "
if (taxid not in tax_profile.tree.data):
raise KeyError(taxid, 'not found in the tree!!!')
ret_val = (((((('\t' * offset) + '<node name="') + taxid) + ':') + tax_profile.tree.data[taxid].name) + '">\n')
offset += 1
if tax_profile.tree.data[taxid].attributes:
if (metric != 'readcount'):
ret_val += (('\t' * offset) + '<readcount>')
for datapoint in dataseries:
if (datapoint in tax_profile.tree.data[taxid].attributes):
ret_val += (('<val>' + format(tax_profile.tree.data[taxid].attributes[datapoint]['count'], '0.0f')) + '</val>')
else:
ret_val += '<val>0</val>'
ret_val += '</readcount>\n'
ret_val += (((('\t' * offset) + '<') + metric) + '>')
for datapoint in dataseries:
if (datapoint in tax_profile.tree.data[taxid].attributes):
ret_val += (('<val>' + format(tax_profile.tree.data[taxid].attributes[datapoint][metric], '0.7f')) + '</val>')
else:
ret_val += '<val>0.0</val>'
ret_val += (((('</' + metric) + '>\n') + ('\t' * offset)) + '<identity>')
for datapoint in dataseries:
if ((datapoint in tax_profile.tree.data[taxid].attributes) and (tax_profile.tree.data[taxid].attributes[datapoint]['hit_count'] > 0)):
ret_val += (('<val>' + format((tax_profile.tree.data[taxid].attributes[datapoint]['identity'] / tax_profile.tree.data[taxid].attributes[datapoint]['hit_count']), '0.1f')) + '</val>')
else:
ret_val += '<val>0.0</val>'
ret_val += '</identity>\n'
gene_ids = set()
for datapoint in tax_profile.tree.data[taxid].attributes:
if ('genes' in tax_profile.tree.data[taxid].attributes[datapoint]):
for gene_id in tax_profile.tree.data[taxid].attributes[datapoint]['genes'].split(' '):
gene_ids.add(gene_id)
ret_val += get_genes_xml(genes, sorted(gene_ids), dataseries, offset, metric)
else:
if (metric != 'readcount'):
ret_val += (('\t' * offset) + '<readcount>')
ret_val += ('<val>0</val>' * len(dataseries))
ret_val += '</readcount>\n'
ret_val += (((('\t' * offset) + '<') + metric) + '>')
ret_val += ('<val>0.0</val>' * len(dataseries))
ret_val += (((('</' + metric) + '>\n') + ('\t' * offset)) + '<identity>')
ret_val += ('<val>0.0%</val>' * len(dataseries))
ret_val += '</identity>\n'
if tax_profile.tree.data[taxid].children:
for child_taxid in tax_profile.tree.data[taxid].children:
ret_val += get_assembly_tax_xml(tax_profile, genes, dataseries, child_taxid, offset, metric)
offset -= 1
ret_val += (('\t' * offset) + '</node>\n')
return ret_val<|docstring|>Returns XML node for assembly phylogenetic tree node and all its children.
Args:
tax_profile (:obj:TaxonomyProfile): taxonomy profile
genes (defaultdict[str,defaultdict[str,dict[str,float]]]): outer key is
gene identifier, middle key is function identifier, inner key is in
[metric, 'count', 'identity', 'coverage', 'Length', 'Completeness'],
value is float (genes[gene_id][function_id][parameter_name] = parameter_value).
dataseries (list of str): function identifiers
taxid (str): taxonomy identifier of a node of interest
offset (int): number of starting tabs
metric (str): scoring metric (default value 'efpkg')
Returns:
ret_val (str): XML node<|endoftext|>
|
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