Api

overrides: 'dict[str, Any] | None' = None,
timeout: 'int | None' = None,
api_key: 'str | None' = None

import wandb

wandb.Api()

(self,
name: 'str',
type: 'str | None' = None)

import wandb

# project、artifactの名、artifactのaliasを指定する
wandb.Api().artifact(name="project/artifact:alias")

# project、artifactの名、特定のartifactバージョンを指定する
wandb.Api().artifact(name="project/artifact:version")

# entity、project、artifactの名、artifactのaliasを指定する
wandb.Api().artifact(name="entity/project/artifact:alias")

# entity、project、artifactの名、特定のartifactバージョンを指定する
wandb.Api().artifact(name="entity/project/artifact:version")

self,
type_name: 'str',
name: 'str'

import wandb

collections = wandb.Api().artifact_collection(
    type_name="type", name="entity/project/artifact_name"
)

# collection 内の最初の artifact を取得する
artifact_example = collections.artifacts()[0]

# artifact の内容を指定したルートディレクトリにダウンロードする。
artifact_example.download()

self,
name: 'str',
type: 'str'

import wandb

wandb.Api.artifact_collection_exists(type="type", name="collection_name")

self,
project_name: 'str',
type_name: 'str',
order: 'str | None' = None,
per_page: 'int' = 50,
start: 'str | None' = None

self,
name: 'str',
type: 'str | None' = None

import wandb

wandb.Api().artifact_exists("entity/project/artifact:version")
wandb.Api().artifact_exists("entity/project/artifact:alias")

self,
type_name: 'str',
project: 'str | None' = None

self,
project: 'str | None' = None,
start: 'str | None' = None

(self, type_name, name, per_page=50)

self,
type_name: 'str',
name: 'str',
order: 'str | None' = None,
per_page: 'int' = 50,
tags: 'list[str] | None' = None,
start: 'str | None' = None

import wandb

wandb.Api().artifacts(type_name="type", name="entity/project/artifact_name")

from itertools import islice

import wandb

api = wandb.Api()

# 最初のページの結果を取得し、カーソルを保存します。
page_size = 10
artifacts = api.artifacts(
    type_name="type",
    name="entity/project/artifact_name",
    per_page=page_size,
)
first_page = list(islice(artifacts, page_size))

saved_cursor = artifacts.cursor

# 後で（例：新しいプロセスで）、保存したカーソルからイテレーションを再開します。
remaining_artifacts = api.artifacts(
    type_name="type",
    name="entity/project/artifact_name",
    per_page=page_size,
    start=saved_cursor,
)

self,
name: 'str', *,
entity: 'str | None' = None

import wandb

api = wandb.Api()
automation = api.automation(name="my-automation")

automation = api.automation(name="other-automation", entity="my-team")

self,
entity: 'str | None' = None, *,
name: 'str | None' = None,
per_page: 'int' = 50,
start: 'str | None' = None

import wandb

api = wandb.Api()
automations = api.automations(entity="my-team")

self,
obj: 'NewAutomation', *,
fetch_existing: 'bool' = False, **kwargs: 'Unpack[WriteAutomationsKwargs]'

import wandb
from wandb.automations import OnRunMetric, RunEvent, SendNotification

api = wandb.Api()

project = api.project("my-project", entity="my-team")

# チームの最初の Slack インテグレーションを使用する
slack_hook = next(api.slack_integrations(entity="my-team"))

event = OnRunMetric(
    scope=project,
    filter=RunEvent.metric("custom-metric") > 10,
)
action = SendNotification.from_integration(slack_hook)

automation = api.create_automation(
    event >> action,
    name="my-automation",
    description="Send a Slack message whenever 'custom-metric' exceeds 10.",
)

self,
entity: 'str',
name: 'str',
display_name: 'str',
spec_type: "Literal['vega2']",
access: "Literal['private', 'public']",
spec: 'str | dict'

    import wandb

    api = wandb.Api()

    # シンプルな棒グラフの仕様を定義する
    vega_spec = {
        "$schema": "https://vega.github.io/schema/vega-lite/v6.json",
        "mark": "bar",
        "data": {"name": "wandb"},
        "encoding": {
            "x": {"field": "${field:x}", "type": "ordinal"},
            "y": {"field": "${field:y}", "type": "quantitative"},
        },
    }

    # カスタムチャートを作成する
    chart_id = api.create_custom_chart(
        entity="my-team",
        name="my-bar-chart",
        display_name="My Custom Bar Chart",
        spec_type="vega2",
        access="private",
        spec=vega_spec,
    )

    # wandb.plot_table() と組み合わせて使用する
    chart = wandb.plot_table(
        vega_spec_name=chart_id,
        data_table=my_table,
        fields={"x": "category", "y": "value"},
    )

self,
name: 'str',
entity: 'str'

self,
name: 'str',
visibility: "Literal['organization', 'restricted']",
organization: 'str | None' = None,
description: 'str | None' = None,
artifact_types: 'list[str] | None' = None

import wandb

api = wandb.Api()
registry = api.create_registry(
    name="my-registry",
    visibility="restricted",
    organization="my-org",
    description="This is a test registry",
    artifact_types=["model"],
)

self, *,
run_id: 'str | None' = None,
project: 'str | None' = None,
entity: 'str | None' = None

self,
name: 'str',
type: 'public.RunQueueResourceType',
entity: 'str | None' = None,
prioritization_mode: 'public.RunQueuePrioritizationMode | None' = None,
config: 'dict | None' = None,
template_variables: 'dict | None' = None

self,
team: 'str',
admin_username: 'str | None' = None

self,
email: 'str',
admin: 'bool | None' = False

self,
obj: 'Automation | str'

(self)

(self,
path: 'str')

import wandb

api = wandb.Api()

project = api.from_path("project")
team_project = api.from_path("team/project")
run = api.from_path("team/project/runs/run_id")
sweep = api.from_path("team/project/sweeps/sweep_id")
report = api.from_path("team/project/reports/report_name")

self,
entity: 'str | None' = None, *,
per_page: 'int' = 50,
start: 'str | None' = None

self,
name: 'str | None',
path: 'str | None' = None

self,
entity: 'str',
project: 'str'

self,
name: 'str | None' = None

self,
name: 'str',
entity: 'str | None' = None

self,
entity: 'str | None' = None,
per_page: 'int' = 200

(self,
entity: 'str',
project: 'str',
queue_name: 'str',
run_queue_item_id: 'str', project_queue=None, priority=None)

self,
organization: 'str | None' = None,
filter: 'dict[str, Any] | None' = None,
order: 'str | None' = None,
per_page: 'int' = 100,
start: 'str | None' = None

import wandb

api = wandb.Api()  # entity が複数の org に属する場合は、org を指定します
api.registries(filter={"name": {"$regex": "model"}})

api.registries().collections(filter={"name": "my_collection", "tag": "my_tag"})

api.registries().collections(
    filter={"name": {"$regex": "my_collection"}}
).versions(filter={"alias": "best"})

api.registries(filter={"name": {"$regex": "model"}}).versions(
    filter={"$or": [{"tag": "prod"}, {"alias": "best"}]}
)

from itertools import islice

import wandb

api = wandb.Api()

# 最初のページの結果を取得し、カーソルを保存します。
page_size = 10
registries = api.registries(per_page=page_size)
first_page = list(islice(registries, page_size))

saved_cursor = registries.cursor

# 後で（例：新しいプロセスで）、保存したカーソルからイテレーションを再開します。
remaining_registries = api.registries(per_page=page_size, start=saved_cursor)

self,
name: 'str',
organization: 'str | None' = None

import wandb

api = wandb.Api()
registry = api.registry(name="my-registry", organization="my-org")
registry.description = "This is an updated description"
registry.save()

self,
path: 'str' = '',
name: 'str | None' = None,
per_page: 'int' = 50

import wandb

wandb.Api.reports("entity/project")

self,
path: 'str' = ''

(self,
entity: 'str',
name: 'str')

(self,
path: 'str | None' = None,
filters: 'dict[str, Any] | None' = None,
order: 'str' = '+created_at',
per_page: 'int' = 50,
include_sweeps: 'bool' = False,
lazy: 'bool' = True)

import wandb
from wandb.apis.public import Api

# project 内で config.experiment_name が "foo" に設定されている run を検索する
Api.runs(path="my_entity/project", filters={"config.experiment_name": "foo"})

# project 内で config.experiment_name が "foo" または "bar" に設定されている run を検索する
Api.runs(
    path="my_entity/project",
    filters={
        "$or": [
            {"config.experiment_name": "foo"},
            {"config.experiment_name": "bar"},
        ]
    },
)

# config.experiment_name が正規表現に一致する project 内の run を検索する
Api.runs(
    path="my_entity/project",
    filters={"config.experiment_name": {"$regex": "b.*"}},
)

# run 名が正規表現に一致する project 内の run を検索する
Api.runs(
    path="my_entity/project", filters={"display_name": {"$regex": "^foo.*"}}
)

# project 内の run を損失の昇順で並べ替えて検索する
Api.runs(path="my_entity/project", order="+summary_metrics.loss")

self, *,
entity: 'str | None' = None,
per_page: 'int' = 50,
start: 'str | None' = None

import wandb

api = wandb.Api()
slack_integrations = api.slack_integrations(entity="my-team")

slack_integrations = api.slack_integrations(entity="my-team")
team_alert_integrations = [
    ig
    for ig in slack_integrations
    if ig.channel_name.startswith("team-alerts-")
]

(self, path='')

(self, root_dir, run_id=None, project=None, entity=None)

self,
team: 'str'

self,
obj: 'Automation', *,
create_missing: 'bool' = False, **kwargs: 'Unpack[WriteAutomationsKwargs]'

import wandb

api = wandb.Api()

automation = api.automation(name="my-automation")
automation.enabled = False
automation.description = "Kept for reference, but no longer used."

updated_automation = api.update_automation(automation)

import wandb

api = wandb.Api()

automation = api.automation(name="my-automation")

updated_automation = api.update_automation(
    automation,
    enabled=False,
    description="Kept for reference, but no longer used.",
)

(self,
name: 'str',
resource_config: 'dict',
resource_type: 'public.RunQueueResourceType',
entity: 'str | None' = None,
template_variables: 'dict | None' = None,
external_links: 'dict | None' = None,
prioritization_mode: 'public.RunQueuePrioritizationMode | None' = None)

self,
username_or_email: 'str'

self,
username_or_email: 'str'

self,
entity: 'str | None' = None, *,
per_page: 'int' = 50,
start: 'str | None' = None

import wandb

api = wandb.Api()
webhook_integrations = api.webhook_integrations(entity="my-team")

webhook_integrations = api.webhook_integrations(entity="my-team")
my_webhooks = [
    ig
    for ig in webhook_integrations
    if ig.url_endpoint.startswith("https://my-fake-url.com")
]