Summary

EnvironmentConfig emits a DeprecationWarning for the memory and storage fields every time it is constructed, even when the caller uses the new memory_mb / storage_mb fields exclusively. The warning originates from Harbor's own handle_deprecated_fields validator, which accesses self.memory and self.storage to check for None — and Pydantic 2 emits a DeprecationWarning on attribute access for any field declared with Field(deprecated=...).

Net effect: any project that runs its test suite under python -W error::DeprecationWarning fails immediately on a clean Harbor 0.7.1 install, even with no use of deprecated fields anywhere in the code or task tomls.

Versions

• Harbor: 0.7.1
• Pydantic: 2.12.5
• Python: 3.14.3

Minimal repro

import warnings
warnings.simplefilter("error", DeprecationWarning)

from harbor.models.task.config import EnvironmentConfig
EnvironmentConfig(docker_image="alpine")

Result:

DeprecationWarning: Use 'memory_mb' instead. This field will be removed in a future version.
  File ".../harbor/models/task/config.py", line 202, in handle_deprecated_fields
    if self.memory is not None:

No deprecated field was set by the caller. The warning fires purely because the validator reads self.memory.

Root cause

harbor/models/task/config.py:

# line 165
memory: str | None = Field(
    default=None,
    deprecated="Use 'memory_mb' instead. This field will be removed in a future version.",
    exclude=True,
)
storage: str | None = Field(
    default=None,
    deprecated="Use 'storage_mb' instead. This field will be removed in a future version.",
    exclude=True,
)

# line 200
@model_validator(mode="after")
def handle_deprecated_fields(self) -> "EnvironmentConfig":
    if self.memory is not None:   # ← Pydantic raises DeprecationWarning here
        ...
    if self.storage is not None:  # ← and here
        ...
    return self

Pydantic 2 wires Field(deprecated=...) such that any attribute read goes through a property that emits the warning. The if self.memory is not None: check inside the validator is itself an attribute access and therefore triggers it — regardless of whether the caller ever provided memory.

Expected behavior

Constructing EnvironmentConfig with only the supported fields (e.g. docker_image="alpine" or memory_mb=512) should not emit any DeprecationWarning. The warning should fire only when the caller actually provided memory= or storage=.

Proposed fix

Read the attribute via __dict__ (or self.model_dump(include={"memory", "storage"})) to bypass the Pydantic deprecation property, or check self.model_fields_set first:

@model_validator(mode="after")
def handle_deprecated_fields(self) -> "EnvironmentConfig":
    # Bypass Field(deprecated=...) attribute property to avoid emitting
    # our own DeprecationWarning when the caller didn't set the field.
    memory = self.__dict__.get("memory")
    if memory is not None:
        warnings.warn(
            "The 'memory' field is deprecated. Use 'memory_mb' instead.",
            DeprecationWarning,
            stacklevel=2,
        )
        self.memory_mb = self._parse_size_to_mb(memory)
        self.__dict__["memory"] = None

    storage = self.__dict__.get("storage")
    if storage is not None:
        warnings.warn(
            "The 'storage' field is deprecated. Use 'storage_mb' instead.",
            DeprecationWarning,
            stacklevel=2,
        )
        self.storage_mb = self._parse_size_to_mb(storage)
        self.__dict__["storage"] = None

    return self

Equivalent alternative using model_fields_set:

if "memory" in self.model_fields_set:
    memory = self.__dict__.get("memory")
    ...

Impact

Downstream projects that run -W error::DeprecationWarning for regression hygiene (catching real deprecations before they bite during dependency upgrades) cannot do so against Harbor 0.7.1 without filtering this specific warning. The workaround is fine short-term but adds noise to project configs.