List your team clusters
gradient clusters list
curl -g -X GET 'https://api.paperspace.io/clusters/getClusters?filter={"limit": 20, "offset": 0, "where": {"isPrivate": true}}' \
-H 'x-api-key: d44808a2785d6a...'
from gradient import ClustersClient
api_key = 'd44808a2785d6a...'
clusters_client = ClustersClient(api_key)
print(clusters_client.list())
| Name | Type | Attributes | Description |
|---|---|---|---|
--limit |
integer | optional | Limit listed clusters per page |
--offset |
integer | optional | Offset value |
--apiKey |
string | optional | API key to use this time only |
--optionsFile |
string | optional | Path to YAML file with predefined options |
--createOptionsFile |
string | optional | Generate template options file |
+-----------+------------------+----------------------------+
| ID | Name | Type |
+-----------+------------------+----------------------------+
| cl9w..... | demo-cluster | Kubernetes Processing Site |
+-----------+------------------+----------------------------+
[
{
id: "cl9w.....",
name: "demo-cluster",
type: "Kubernetes Processing Site",
region: "private",
cloud: "paperspace-cloud",
teamId: "tewr3st2z",
isDefault: false,
dtCreated: "2020-04-22T20:39:24.004Z",
dtModified: "2021-07-16T21:02:47.433Z",
...
},
]
[
Cluster(
(id = "cl9w....."),
(name = "demo-cluster"),
(type = "Kubernetes Processing Site")
),
];
List available machine types
gradient clusters machineTypes list
curl -X GET 'https://api.paperspace.io/vmTypes/getVmTypesByClusters' \
-H 'x-api-key: d44808a2785d6a...'
from gradient import MachineTypesClient
api_key = 'd44808a2785d6a...'
machineTypes_client = MachineTypesClient(api_key)
print(machineTypes_client.list())
| Name | Type | Attributes | Description |
|---|---|---|---|
--clusterId |
string | optional | Filter machine types by cluster ID |
--apiKey |
string | optional | API key to use this time only |
--optionsFile |
string | optional | Path to YAML file with predefined options |
--createOptionsFile |
string | optional | Generate template options file |
+-------------+--------------+-----------+--------------+-----------+--------------+--------------------------------------------+
| Name | Kind | CPU Count | RAM [Bytes] | GPU Count | GPU Model | Clusters |
+-------------+--------------+-----------+--------------+-----------+--------------+--------------------------------------------+
| P4000 | p4000 | 8 | 32212254720 | 1 | Quadro P4000 | cl9w..... |
| P5000 | p5000 | 8 | 32212254720 | 1 | Quadro P5000 | cl9w..... |
| V100 | v100 | 8 | 32212254720 | 1 | Tesla V100 | cl9w..... |
+-------------+--------------+-----------+--------------+-----------+--------------+--------------------------------------------+
[
VmType(
(label = "P4000"),
(kind = "p4000"),
(cpu_count = 8),
(ram_in_bytes = 32212254720),
(gpu_count = 1),
(gpu_model = VmTypeGpuModel(
(label = "Quadro P4000"),
(model = "passthrough"),
(memory_in_bytes = 8589934592)
)),
(is_preemptible = False),
(deployment_type = "gpu"),
(deployment_size = "small"),
(clusters = ["cl9w....."])
),
VmType(
(label = "P5000"),
(kind = "p5000"),
(cpu_count = 8),
(ram_in_bytes = 32212254720),
(gpu_count = 1),
(gpu_model = VmTypeGpuModel(
(label = "Quadro P5000"),
(model = "passthrough"),
(memory_in_bytes = 17179869184)
)),
(is_preemptible = False),
(deployment_type = "gpu"),
(deployment_size = "medium"),
(clusters = ["cl92....."])
),
VmType(
(label = "V100"),
(kind = "v100"),
(cpu_count = 8),
(ram_in_bytes = 32212254720),
(gpu_count = 1),
(gpu_model = VmTypeGpuModel(
(label = "Tesla V100"),
(model = "passthrough"),
(memory_in_bytes = 17179869184)
)),
(is_preemptible = False),
(deployment_type = "gpu"),
(deployment_size = "large"),
(clusters = ["cl9w....."])
),
];
[
VmType(
(label = "P4000"),
(kind = "p4000"),
(cpu_count = 8),
(ram_in_bytes = 32212254720),
(gpu_count = 1),
(gpu_model = VmTypeGpuModel(
(label = "Quadro P4000"),
(model = "passthrough"),
(memory_in_bytes = 8589934592)
)),
(is_preemptible = False),
(deployment_type = "gpu"),
(deployment_size = "small"),
(clusters = ["cl9w....."])
),
VmType(
(label = "P5000"),
(kind = "p5000"),
(cpu_count = 8),
(ram_in_bytes = 32212254720),
(gpu_count = 1),
(gpu_model = VmTypeGpuModel(
(label = "Quadro P5000"),
(model = "passthrough"),
(memory_in_bytes = 17179869184)
)),
(is_preemptible = False),
(deployment_type = "gpu"),
(deployment_size = "medium"),
(clusters = ["cl92....."])
),
VmType(
(label = "V100"),
(kind = "v100"),
(cpu_count = 8),
(ram_in_bytes = 32212254720),
(gpu_count = 1),
(gpu_model = VmTypeGpuModel(
(label = "Tesla V100"),
(model = "passthrough"),
(memory_in_bytes = 17179869184)
)),
(is_preemptible = False),
(deployment_type = "gpu"),
(deployment_size = "large"),
(clusters = ["cl9w....."])
),
];