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openml._api.resources.run #

RunV1API #

RunV1API(http: HTTPClient, minio: MinIOClient)

Bases: ResourceV1API, RunAPI

Version 1 API implementation for run resources.

Source code in openml/_api/resources/base/base.py 
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def __init__(self, http: HTTPClient, minio: MinIOClient):
    self._http = http
    self._minio = minio

delete #

delete(resource_id: int) -> bool

Delete a resource using the V1 API.

PARAMETER DESCRIPTION
resource_id

Identifier of the resource to delete.

TYPE: int

RETURNS DESCRIPTION
bool

True if the server confirms successful deletion.
RAISES DESCRIPTION
ValueError

If the resource type is not supported for deletion.
OpenMLNotAuthorizedError

If the user is not permitted to delete the resource.
OpenMLServerError

If deletion fails for an unknown reason.
OpenMLServerException

For other server-side errors.
Source code in openml/_api/resources/base/versions.py 
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def delete(self, resource_id: int) -> bool:
    """
    Delete a resource using the V1 API.

    Parameters
    ----------
    resource_id : int
        Identifier of the resource to delete.

    Returns
    -------
    bool
        ``True`` if the server confirms successful deletion.

    Raises
    ------
    ValueError
        If the resource type is not supported for deletion.
    OpenMLNotAuthorizedError
        If the user is not permitted to delete the resource.
    OpenMLServerError
        If deletion fails for an unknown reason.
    OpenMLServerException
        For other server-side errors.
    """
    if self.resource_type not in _LEGAL_RESOURCES_DELETE:
        raise ValueError(f"Can't delete a {self.resource_type.value}")

    endpoint_name = self._get_endpoint_name()
    path = f"{endpoint_name}/{resource_id}"
    try:
        response = self._http.delete(path)
        result = xmltodict.parse(response.content)
        return f"oml:{endpoint_name}_delete" in result
    except OpenMLServerException as e:
        self._handle_delete_exception(endpoint_name, e)
        raise

publish #

publish(path: str, files: Mapping[str, Any] | None) -> int

Publish a new resource using the V1 API.

PARAMETER DESCRIPTION
path

API endpoint path for the upload.

TYPE: str

files

Files to upload as part of the request payload.

TYPE: Mapping of str to Any or None

RETURNS DESCRIPTION
int

Identifier of the newly created resource.
RAISES DESCRIPTION
ValueError

If the server response does not contain a valid resource ID.
OpenMLServerException

If the server returns an error during upload.
Source code in openml/_api/resources/base/versions.py 
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def publish(self, path: str, files: Mapping[str, Any] | None) -> int:
    """
    Publish a new resource using the V1 API.

    Parameters
    ----------
    path : str
        API endpoint path for the upload.
    files : Mapping of str to Any or None
        Files to upload as part of the request payload.

    Returns
    -------
    int
        Identifier of the newly created resource.

    Raises
    ------
    ValueError
        If the server response does not contain a valid resource ID.
    OpenMLServerException
        If the server returns an error during upload.
    """
    response = self._http.post(path, files=files)
    parsed_response = xmltodict.parse(response.content)
    return self._extract_id_from_upload(parsed_response)

tag #

tag(resource_id: int, tag: str) -> list[str]

Add a tag to a resource using the V1 API.

PARAMETER DESCRIPTION
resource_id

Identifier of the resource to tag.

TYPE: int

tag

Tag to associate with the resource.

TYPE: str

RETURNS DESCRIPTION
list of str

Updated list of tags assigned to the resource.
RAISES DESCRIPTION
ValueError

If the resource type does not support tagging.
OpenMLServerException

If the server returns an error.
Source code in openml/_api/resources/base/versions.py 
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def tag(self, resource_id: int, tag: str) -> list[str]:
    """
    Add a tag to a resource using the V1 API.

    Parameters
    ----------
    resource_id : int
        Identifier of the resource to tag.
    tag : str
        Tag to associate with the resource.

    Returns
    -------
    list of str
        Updated list of tags assigned to the resource.

    Raises
    ------
    ValueError
        If the resource type does not support tagging.
    OpenMLServerException
        If the server returns an error.
    """
    if self.resource_type not in _LEGAL_RESOURCES_TAG:
        raise ValueError(f"Can't tag a {self.resource_type.value}")

    endpoint_name = self._get_endpoint_name()
    path = f"{endpoint_name}/tag"
    data = {f"{endpoint_name}_id": resource_id, "tag": tag}
    response = self._http.post(path, data=data)

    parsed_response = xmltodict.parse(response.content, force_list={"oml:tag"})
    result = parsed_response[f"oml:{endpoint_name}_tag"]
    tags: list[str] = result.get("oml:tag", [])

    return tags

untag #

untag(resource_id: int, tag: str) -> list[str]

Remove a tag from a resource using the V1 API.

PARAMETER DESCRIPTION
resource_id

Identifier of the resource to untag.

TYPE: int

tag

Tag to remove from the resource.

TYPE: str

RETURNS DESCRIPTION
list of str

Updated list of tags assigned to the resource.
RAISES DESCRIPTION
ValueError

If the resource type does not support tagging.
OpenMLServerException

If the server returns an error.
Source code in openml/_api/resources/base/versions.py 
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def untag(self, resource_id: int, tag: str) -> list[str]:
    """
    Remove a tag from a resource using the V1 API.

    Parameters
    ----------
    resource_id : int
        Identifier of the resource to untag.
    tag : str
        Tag to remove from the resource.

    Returns
    -------
    list of str
        Updated list of tags assigned to the resource.

    Raises
    ------
    ValueError
        If the resource type does not support tagging.
    OpenMLServerException
        If the server returns an error.
    """
    if self.resource_type not in _LEGAL_RESOURCES_TAG:
        raise ValueError(f"Can't untag a {self.resource_type.value}")

    endpoint_name = self._get_endpoint_name()
    path = f"{endpoint_name}/untag"
    data = {f"{endpoint_name}_id": resource_id, "tag": tag}
    response = self._http.post(path, data=data)

    parsed_response = xmltodict.parse(response.content, force_list={"oml:tag"})
    result = parsed_response[f"oml:{endpoint_name}_untag"]
    tags: list[str] = result.get("oml:tag", [])

    return tags

RunV2API #

RunV2API(http: HTTPClient, minio: MinIOClient)

Bases: ResourceV2API, RunAPI

Version 2 API implementation for run resources.

Source code in openml/_api/resources/base/base.py 
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def __init__(self, http: HTTPClient, minio: MinIOClient):
    self._http = http
    self._minio = minio