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tamirsetamirse
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Merge branch 'master' into refactor/use-dataclasses
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‎CHANGELOG.rst‎

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Changelog
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=========
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* Added environment variables to container deployment example
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* Updated examples image from 'fastai' to 'ubuntu-24.04-cuda-12.8-open-docker'
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* Consistent naming and load of credentials from env variables in examples
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v1.8.4 (2025-03-25)
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-------------------
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‎README.md‎

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@@ -54,7 +54,7 @@ DataCrunch's Public API documentation [is available here](https://api.datacrunch
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# Create a new instance
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instance = datacrunch.instances.create(instance_type='1V100.6V',
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image='fastai',
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image='ubuntu-24.04-cuda-12.8-open-docker',
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ssh_key_ids=ssh_keys,
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hostname='example',
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description='example instance')

‎datacrunch/datacrunch.py‎

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@@ -28,6 +28,11 @@ def __init__(self, client_id: str, client_secret: str, base_url: str = "https://
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:type base_url: str, optional
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"""
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# Validate that client_id and client_secret are not empty
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if not client_id or not client_secret:
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raise ValueError(
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"client_id and client_secret must be provided")
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# Constants
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self.constants: Constants = Constants(base_url, VERSION)
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"""Constants"""

‎docs/source/examples/advanced_create_instance.rst‎

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if price_per_hour * DURATION < balance.amount:
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# Deploy a new 8V instance
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instance = datacrunch.instances.create(instance_type=INSTANCE_TYPE_8V,
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image='fastai',
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image='ubuntu-24.04-cuda-12.8-open-docker',
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ssh_key_ids=ssh_keys_ids,
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hostname='example',
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description='large instance'
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else:
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# Deploy a new 4V instance
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instance = datacrunch.instances.create(instance_type=INSTANCE_TYPE_4V,
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image='fastai',
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image='ubuntu-24.04-cuda-12.8-open-docker',
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ssh_key_ids=ssh_keys_ids,
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hostname='example',
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description='medium instance')

‎docs/source/examples/instance_actions.rst‎

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# Create a new 1V100.6V instance
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instance = datacrunch.instances.create(instance_type='1V100.6V',
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image='fastai',
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image='ubuntu-24.04-cuda-12.8-open-docker',
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ssh_key_ids=ssh_keys_ids,
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hostname='example',
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description='example instance')

‎docs/source/examples/instances_and_volumes.rst‎

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# Create instance with extra attached volumes
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instance_with_extra_volumes = datacrunch.instances.create(instance_type='1V100.6V',
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image='fastai',
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image='ubuntu-24.04-cuda-12.8-open-docker',
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ssh_key_ids=ssh_keys,
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hostname='example',
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description='example instance',
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# Create instance with custom OS volume size and name
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instance_with_custom_os_volume = datacrunch.instances.create(instance_type='1V100.6V',
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image='fastai',
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image='ubuntu-24.04-cuda-12.8-open-docker',
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ssh_key_ids=ssh_keys,
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hostname='example',
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description='example instance',

‎docs/source/examples/simple_create_instance.rst‎

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# Create a new instance
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instance = datacrunch.instances.create(instance_type='1V100.6V',
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image='fastai',
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image='ubuntu-24.04-cuda-12.8-open-docker',
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ssh_key_ids=ssh_keys_ids,
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hostname='example',
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description='example instance')

‎docs/source/index.rst‎

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# Create a new instance
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instance = datacrunch.instances.create(instance_type='1V100.6V',
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image='fastai',
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image='ubuntu-24.04-cuda-12.8-open-docker',
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ssh_key_ids=ssh_keys_ids,
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hostname='example',
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description='example instance')

‎examples/advanced_create_instance.py‎

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# Arbitrary duration for the example
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DURATION = 24 * 7 # one week
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# Get client secret from environment variable
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CLIENT_SECRET = os.environ['DATACRUNCH_CLIENT_SECRET']
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CLIENT_ID = 'Ibk5bdxV64lKAWOqYnvSi' # Replace with your client ID
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# Get client secret and id from environment variables
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DATACRUNCH_CLIENT_ID = os.environ.get('DATACRUNCH_CLIENT_ID')
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DATACRUNCH_CLIENT_SECRET = os.environ.get('DATACRUNCH_CLIENT_SECRET')
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try:
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# Create datcrunch client
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datacrunch = DataCrunchClient(CLIENT_ID, CLIENT_SECRET)
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datacrunch = DataCrunchClient(
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DATACRUNCH_CLIENT_ID, DATACRUNCH_CLIENT_SECRET)
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# Create new SSH key
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public_key = 'ssh-ed25519 AAAAC3NzaC1lZDI1NTE5AAAAI0qq2Qjt5GPi7DKdcnBHOkvk8xNsG9dA607tnWagOkHC test_key'
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if price_per_hour * DURATION < balance.amount:
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# Deploy a new 8V instance
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instance = datacrunch.instances.create(instance_type=INSTANCE_TYPE_8V,
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image='fastai',
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image='ubuntu-24.04-cuda-12.8-open-docker',
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ssh_key_ids=ssh_keys_ids,
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hostname='example',
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description='large instance',
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os_volume={
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"name": "Large OS volume",
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"size": 95
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})
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"name": "Large OS volume",
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"size": 95
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})
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else:
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# Deploy a new 4V instance
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instance = datacrunch.instances.create(instance_type=INSTANCE_TYPE_4V,
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image='fastai',
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image='ubuntu-24.04-cuda-12.8-open-docker',
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ssh_key_ids=ssh_keys_ids,
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hostname='example',
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description='medium instance')

‎examples/containers/compute_resources_example.py‎

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import os
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from datacrunch import DataCrunchClient
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from typing import List
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from datacrunch.containers.containers import ComputeResource
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# Get client secret and id from environment variables
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DATACRUNCH_CLIENT_ID = os.environ.get('DATACRUNCH_CLIENT_ID')
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DATACRUNCH_CLIENT_SECRET = os.environ.get('DATACRUNCH_CLIENT_SECRET')
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def list_all_compute_resources(client: DataCrunchClient) -> List[ComputeResource]:
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"""List all available compute resources.
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def main():
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# Initialize the client with your credentials
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client = DataCrunchClient(
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client_id="your_client_id",
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client_secret="your_client_secret"
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)
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datacrunch = DataCrunchClient(
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DATACRUNCH_CLIENT_ID, DATACRUNCH_CLIENT_SECRET)
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# Example 1: List all compute resources
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print("\nAll compute resources:")
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all_resources = list_all_compute_resources(client)
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print("All compute resources:")
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all_resources = list_all_compute_resources(datacrunch)
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for resource in all_resources:
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print(
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f"Name: {resource.name}, Size: {resource.size}, Available: {resource.is_available}")
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# Example 2: List available compute resources
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print("\nAvailable compute resources:")
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available_resources = list_available_compute_resources(client)
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print("Available compute resources:")
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available_resources = list_available_compute_resources(datacrunch)
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for resource in available_resources:
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print(f"Name: {resource.name}, Size: {resource.size}")
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# Example 3: List compute resources of size 8
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print("\nCompute resources with size 8:")
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size_8_resources = list_compute_resources_by_size(client, 8)
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print("Compute resources with size 8:")
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size_8_resources = list_compute_resources_by_size(datacrunch, 8)
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for resource in size_8_resources:
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print(f"Name: {resource.name}, Available: {resource.is_available}")
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