[Verda] Rename the datacrunch backend to verda

contributing/BACKENDS.md

@@ -42,7 +42,7 @@ base class. See its docstrings for descriptions of the methods that your class s
 
 Refer to examples:
 - Offline providers:
-  [datacrunch.py](https://github.com/dstackai/gpuhunt/blob/main/src/gpuhunt/providers/datacrunch.py),
+  [verda.py](https://github.com/dstackai/gpuhunt/blob/main/src/gpuhunt/providers/verda.py),
   [aws.py](https://github.com/dstackai/gpuhunt/blob/main/src/gpuhunt/providers/aws.py),
   [azure.py](https://github.com/dstackai/gpuhunt/blob/main/src/gpuhunt/providers/azure.py),
   [lambdalabs.py](https://github.com/dstackai/gpuhunt/blob/main/src/gpuhunt/providers/lambdalabs.py).
@@ -64,7 +64,7 @@ Add your provider in the following places:
 For offline providers, you can add data quality tests under `src/integrity_tests/`.
 Data quality tests are run after collecting offline catalogs to ensure their integrity.
 
-Refer to examples: [test_datacrunch.py](https://github.com/dstackai/gpuhunt/blob/main/src/integrity_tests/test_datacrunch.py),
+Refer to examples: [test_verda.py](https://github.com/dstackai/gpuhunt/blob/main/src/integrity_tests/test_verda.py),
 [test_gcp.py](https://github.com/dstackai/gpuhunt/blob/main/src/integrity_tests/test_gcp.py).
 
 ### 1.6. Submit a pull request
@@ -125,7 +125,7 @@ Then add these models to `AnyBackendConfig*` unions in [`src/dstack/_internal/co
 The script also generates `*BackendStoredConfig` that extends `*BackendConfig` to be able to store extra parameters in the DB. By the same logic, it generates `*Config` that extends `*BackendStoredConfig` with creds and uses it as the main `Backend` and `Compute` config instead of using `*BackendConfigWithCreds` directly.
 
 Refer to examples:
-[datacrunch](https://github.com/dstackai/dstack/blob/master/src/dstack/_internal/core/backends/datacrunch/models.py),
+[verda](https://github.com/dstackai/dstack/blob/master/src/dstack/_internal/core/backends/verda/models.py),
 [aws](https://github.com/dstackai/dstack/blob/master/src/dstack/_internal/core/backends/aws/models.py),
 [gcp](https://github.com/dstackai/dstack/blob/master/src/dstack/_internal/core/backends/gcp/models.py),
 [azure](https://github.com/dstackai/dstack/blob/master/src/dstack/_internal/core/backends/models.py), etc.
@@ -136,7 +136,7 @@ Go to `compute.py` and implement `Compute` methods.
 Optionally, extend and implement `ComputeWith*` classes to support additional features such as fleets, volumes, gateways, placement groups, etc. For example, extend `ComputeWithCreateInstanceSupport` to support fleets.
 
 Refer to examples:
-[datacrunch](https://github.com/dstackai/dstack/blob/master/src/dstack/_internal/core/backends/datacrunch/compute.py),
+[verda](https://github.com/dstackai/dstack/blob/master/src/dstack/_internal/core/backends/verda/compute.py),
 [aws](https://github.com/dstackai/dstack/blob/master/src/dstack/_internal/core/backends/aws/compute.py),
 [gcp](https://github.com/dstackai/dstack/blob/master/src/dstack/_internal/core/backends/gcp/compute.py),
 [azure](https://github.com/dstackai/dstack/blob/master/src/dstack/_internal/core/backends/azure/compute.py), etc.
@@ -146,7 +146,7 @@ Refer to examples:
 Go to `configurator.py` and implement custom `Configurator` logic. At minimum, you should implement creds validation.
 You may also need to validate other config parameters if there are any.
 
-Refer to examples: [datacrunch](https://github.com/dstackai/dstack/blob/master/src/dstack/_internal/core/backends/datacrunch/configurator.py),
+Refer to examples: [verda](https://github.com/dstackai/dstack/blob/master/src/dstack/_internal/core/backends/verda/configurator.py),
 [aws](https://github.com/dstackai/dstack/blob/master/src/dstack/_internal/core/backends/aws/configurator.py),
 [gcp](https://github.com/dstackai/dstack/blob/master/src/dstack/_internal/core/backends/gcp/configurator.py),
 [azure](https://github.com/dstackai/dstack/blob/master/src/dstack/_internal/core/backends/azure/configurator.py), etc.
@@ -195,7 +195,7 @@ For some VM-based backends, the `dstack` team also maintains
 [custom VM images](../scripts/packer/README.md) with the required dependencies
 and `dstack`-specific optimizations.
 
-Examples of VM-based backends include: `aws`, `azure`, `gcp`, `lambda`, `datacrunch`, `tensordock`, etc.
+Examples of VM-based backends include: `aws`, `azure`, `gcp`, `lambda`, `verda`, etc.
 
 #### 3.1.2. Container-based backend compute type
 

contributing/GPUHUNT.md

@@ -65,7 +65,7 @@ Some providers offer extreme flexibility in possible configurations, but not all
 - Filters out if: outdated family, not supported family
 - Queries configuration details to fill CPU, RAM, and GPU information
 
-### DataCrunch
+### Verda
 
 - Just queries all offers via API
 

docs/docs/concepts/backends.md

@@ -854,9 +854,11 @@ There are two ways to configure OCI: using client credentials or using the defau
         compartment_id: ocid1.compartment.oc1..aaaaaaaa
     ```
 
-### DataCrunch
+<span id="datacrunch"></span>
 
-Log into your [DataCrunch](https://cloud.datacrunch.io/) account, click Keys in the sidebar, find `REST API Credentials` area and then click the `Generate Credentials` button.
+### Verda (formerly DataCrunch) { #verda }
+
+Log into your [Verda](https://console.verda.com/signin) account, click Keys in the sidebar, find `REST API Credentials` area and then click the `Generate Credentials` button.
 
 Then, go ahead and configure the backend:
 

docs/docs/reference/server/config.yml.md

@@ -258,18 +258,18 @@ to configure [backends](../../concepts/backends.md) and other [server-level sett
         type:
             required: true
 
-##### `projects[n].backends[type=datacrunch]` { #datacrunch data-toc-label="datacrunch" }
+##### `projects[n].backends[type=verda]` { #verda data-toc-label="verda" }
 
-#SCHEMA# dstack._internal.core.backends.datacrunch.models.DataCrunchBackendConfigWithCreds
+#SCHEMA# dstack._internal.core.backends.verda.models.VerdaBackendConfigWithCreds
     overrides:
         show_root_heading: false
         type:
             required: true
-        item_id_prefix: datacrunch-
+        item_id_prefix: verda-
 
-###### `projects[n].backends[type=datacrunch].creds` { #datacrunch-creds data-toc-label="creds" }
+###### `projects[n].backends[type=verda].creds` { #verda-creds data-toc-label="creds" }
 
-#SCHEMA# dstack._internal.core.backends.datacrunch.models.DataCrunchAPIKeyCreds
+#SCHEMA# dstack._internal.core.backends.verda.models.VerdaAPIKeyCreds
     overrides:
         show_root_heading: false
         type:

docs/partners.md

@@ -95,9 +95,9 @@ hide:
     </span> -->
 
     <span class="feature-cell" target="_blank">
-        <img width="52" style="margin: 10px -4px;" src="/assets/images/datacrunch-logo.svg">
+        <img width="42" src="/assets/images/verda-logo.svg">
         <h3>
-            DataCrunch
+            Verda
         </h3>
     </span>
 </div>

pyproject.toml

@@ -32,7 +32,7 @@ dependencies = [
     "python-multipart>=0.0.16",
     "filelock",
     "psutil",
-    "gpuhunt==0.1.14",
+    "gpuhunt==0.1.15",
     "argcomplete>=3.5.0",
     "ignore-python>=0.2.0",
     "orjson",
@@ -186,7 +186,11 @@ gcp = [
     "dstack[server]",
 ]
 datacrunch = [
-    "datacrunch",
+    "verda; python_version >= '3.10'",
+    "dstack[server]",
+]
+verda = [
+    "verda; python_version >= '3.10'",
     "dstack[server]",
 ]
 kubernetes = [
@@ -211,5 +215,5 @@ nebius = [
     "dstack[server]",
 ]
 all = [
-    "dstack[gateway,server,aws,azure,gcp,datacrunch,kubernetes,lambda,nebius,oci]",
+    "dstack[gateway,server,aws,azure,gcp,verda,kubernetes,lambda,nebius,oci]",
 ]

src/dstack/_internal/core/backends/base/offers.py

@@ -39,6 +39,8 @@ def get_catalog_offers(
     catalog: Optional[gpuhunt.Catalog] = None,
 ) -> List[InstanceOffer]:
     provider = backend.value
+    if backend == BackendType.DATACRUNCH:
+        provider = BackendType.VERDA.value  # Backward compatibility
     if backend == BackendType.LAMBDA:
         provider = "lambdalabs"
     if backend == BackendType.AMDDEVCLOUD:

src/dstack/_internal/core/backends/configurators.py

@@ -127,6 +127,15 @@
 except ImportError:
     pass
 
+try:
+    from dstack._internal.core.backends.verda.configurator import (
+        VerdaConfigurator,
+    )
+
+    _CONFIGURATOR_CLASSES.append(VerdaConfigurator)
+except ImportError:
+    pass
+
 try:
     from dstack._internal.core.backends.vultr.configurator import VultrConfigurator
 

src/dstack/_internal/core/backends/datacrunch/__init__.py

@@ -0,0 +1 @@
+# DataCrunch backend for backward compatibility

src/dstack/_internal/core/backends/datacrunch/backend.py

@@ -1,16 +1,18 @@
-from dstack._internal.core.backends.base.backend import Backend
 from dstack._internal.core.backends.datacrunch.compute import DataCrunchCompute
-from dstack._internal.core.backends.datacrunch.models import DataCrunchConfig
+from dstack._internal.core.backends.verda.backend import VerdaBackend
+from dstack._internal.core.backends.verda.models import VerdaConfig
 from dstack._internal.core.models.backends.base import BackendType
 
 
-class DataCrunchBackend(Backend):
+# Deprecated
+# TODO: Remove in 0.21
+class DataCrunchBackend(VerdaBackend):
     TYPE = BackendType.DATACRUNCH
     COMPUTE_CLASS = DataCrunchCompute
 
-    def __init__(self, config: DataCrunchConfig):
+    def __init__(self, config: VerdaConfig):
         self.config = config
-        self._compute = DataCrunchCompute(self.config)
+        self._compute = DataCrunchCompute(self.config, self.TYPE)
 
     def compute(self) -> DataCrunchCompute:
         return self._compute