Analytics and Query API

• 1: api
• 2: artifacts
• 3: automations
• 4: files
• 5: history
• 6: integrations
• 7: jobs
• 8: projects
• 9: query_generator
• 10: reports
• 11: runs
• 12: sweeps
• 13: teams
• 14: users

1 - api

module wandb.apis.public

Use the Public API to export or update data that you have saved to W&B.

Before using this API, you’ll want to log data from your script — check the Quickstart for more details.

You might use the Public API to

• update metadata or metrics for an experiment after it has been completed,
• pull down your results as a dataframe for post-hoc analysis in a Jupyter notebook, or
• check your saved model artifacts for those tagged as ready-to-deploy.

For more on using the Public API, check out our guide.

class RetryingClient

method RetryingClient.__init__

__init__(client: wandb_gql.client.Client)

property RetryingClient.app_url

property RetryingClient.server_info

method RetryingClient.execute

execute(*args, **kwargs)

method RetryingClient.version_supported

version_supported(min_version: str) → bool

class Api

Used for querying the W&B server.

Examples:

import wandb

wandb.Api()

method Api.__init__

__init__(
    overrides: Optional[Dict[str, Any]] = None,
    timeout: Optional[int] = None,
    api_key: Optional[str] = None
) → None

Initialize the API.

Args:

• overrides (dict[str, Any] | None): You can set base_url if you are
• using a W&B server other than https: //api.wandb.ai. You can also set defaults for entity, project, and run.
• timeout (int | None): HTTP timeout in seconds for API requests. If not specified, the default timeout will be used.
• api_key (str | None): API key to use for authentication. If not provided, the API key from the current environment or configuration will be used.

property Api.api_key

Returns W&B API key.

property Api.client

Returns the client object.

property Api.default_entity

Returns the default W&B entity.

property Api.user_agent

Returns W&B public user agent.

property Api.viewer

Returns the viewer object.

method Api.artifact

artifact(name: str, type: Optional[str] = None)

Returns a single artifact.

Args:

• name: The artifact’s name. The name of an artifact resembles a filepath that consists, at a minimum, the name of the project the artifact was logged to, the name of the artifact, and the artifact’s version or alias. Optionally append the entity that logged the artifact as a prefix followed by a forward slash. If no entity is specified in the name, the Run or API setting’s entity is used.
• type: The type of artifact to fetch.

Returns: An Artifact object.

Raises:

• ValueError: If the artifact name is not specified.
• ValueError: If the artifact type is specified but does not match the type of the fetched artifact.

Examples: In the proceeding code snippets “entity”, “project”, “artifact”, “version”, and “alias” are placeholders for your W&B entity, name of the project the artifact is in, the name of the artifact, and artifact’s version, respectively.

import wandb

# Specify the project, artifact's name, and the artifact's alias
wandb.Api().artifact(name="project/artifact:alias")

# Specify the project, artifact's name, and a specific artifact version
wandb.Api().artifact(name="project/artifact:version")

# Specify the entity, project, artifact's name, and the artifact's alias
wandb.Api().artifact(name="entity/project/artifact:alias")

# Specify the entity, project, artifact's name, and a specific artifact version
wandb.Api().artifact(name="entity/project/artifact:version")

Note:

This method is intended for external use only. Do not call api.artifact() within the wandb repository code.

method Api.artifact_collection

artifact_collection(type_name: str, name: str) → public.ArtifactCollection

Returns a single artifact collection by type.

You can use the returned ArtifactCollection object to retrieve information about specific artifacts in that collection, and more.

Args:

• type_name: The type of artifact collection to fetch.
• name: An artifact collection name. Optionally append the entity that logged the artifact as a prefix followed by a forward slash.

Returns: An ArtifactCollection object.

Examples: In the proceeding code snippet “type”, “entity”, “project”, and “artifact_name” are placeholders for the collection type, your W&B entity, name of the project the artifact is in, and the name of the artifact, respectively.

import wandb

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

# Get the first artifact in the collection
artifact_example = collections.artifacts()[0]

# Download the contents of the artifact to the specified root directory.
artifact_example.download()

method Api.artifact_collection_exists

artifact_collection_exists(name: str, type: str) → bool

Whether an artifact collection exists within a specified project and entity.

Args:

• name: An artifact collection name. Optionally append the entity that logged the artifact as a prefix followed by a forward slash. If entity or project is not specified, infer the collection from the override params if they exist. Otherwise, entity is pulled from the user settings and project will default to “uncategorized”.
• type: The type of artifact collection.

Returns: True if the artifact collection exists, False otherwise.

Examples: In the proceeding code snippet “type”, and “collection_name” refer to the type of the artifact collection and the name of the collection, respectively.

import wandb

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

method Api.artifact_collections

artifact_collections(
    project_name: str,
    type_name: str,
    per_page: int = 50
) → public.ArtifactCollections

Returns a collection of matching artifact collections.

Args:

• project_name: The name of the project to filter on.
• type_name: The name of the artifact type to filter on.
• per_page: Sets the page size for query pagination. None will use the default size. Usually there is no reason to change this.

Returns: An iterable ArtifactCollections object.

method Api.artifact_exists

artifact_exists(name: str, type: Optional[str] = None) → bool

Whether an artifact version exists within the specified project and entity.

Args:

• name: The name of artifact. Add the artifact’s entity and project as a prefix. Append the version or the alias of the artifact with a colon. If the entity or project is not specified, W&B uses override parameters if populated. Otherwise, the entity is pulled from the user settings and the project is set to “Uncategorized”.
• type: The type of artifact.

Returns: True if the artifact version exists, False otherwise.

Examples: In the proceeding code snippets “entity”, “project”, “artifact”, “version”, and “alias” are placeholders for your W&B entity, name of the project the artifact is in, the name of the artifact, and artifact’s version, respectively.

import wandb

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

method Api.artifact_type

artifact_type(
    type_name: str,
    project: Optional[str] = None
) → public.ArtifactType

Returns the matching ArtifactType.

Args:

• type_name: The name of the artifact type to retrieve.
• project: If given, a project name or path to filter on.

Returns: An ArtifactType object.

method Api.artifact_types

artifact_types(project: Optional[str] = None) → public.ArtifactTypes

Returns a collection of matching artifact types.

Args:

• project: The project name or path to filter on.

Returns: An iterable ArtifactTypes object.

method Api.artifact_versions

artifact_versions(type_name, name, per_page=50)

Deprecated. Use Api.artifacts(type_name, name) method instead.

method Api.artifacts

artifacts(
    type_name: str,
    name: str,
    per_page: int = 50,
    tags: Optional[List[str]] = None
) → public.Artifacts

Return an Artifacts collection.

Args: type_name: The type of artifacts to fetch. name: The artifact’s collection name. Optionally append the entity that logged the artifact as a prefix followed by a forward slash. per_page: Sets the page size for query pagination. If set to None, use the default size. Usually there is no reason to change this. tags: Only return artifacts with all of these tags.

Returns: An iterable Artifacts object.

Examples: In the proceeding code snippet, “type”, “entity”, “project”, and “artifact_name” are placeholders for the artifact type, W&B entity, name of the project the artifact was logged to, and the name of the artifact, respectively.

import wandb

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

method Api.automation

automation(name: str, entity: Optional[str] = None) → Automation

Returns the only Automation matching the parameters.

Args:

• name: The name of the automation to fetch.
• entity: The entity to fetch the automation for.

Raises:

• ValueError: If zero or multiple Automations match the search criteria.

Examples: Get an existing automation named “my-automation”:

    import wandb

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

Get an existing automation named "other-automation", from the entity "my-team": 

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

---

### <kbd>method</kbd> `Api.automations`

```python
automations(
    entity: Optional[str] = None,
    name: Optional[str] = None,
    per_page: int = 50
) → Iterator[ForwardRef('Automation')]

Returns an iterator over all Automations that match the given parameters.

If no parameters are provided, the returned iterator will contain all Automations that the user has access to.

Args:

• entity: The entity to fetch the automations for.
• name: The name of the automation to fetch.
• per_page: The number of automations to fetch per page. Defaults to 50. Usually there is no reason to change this.

Returns: A list of automations.

Examples: Fetch all existing automations for the entity “my-team”:

    import wandb

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

---

### <kbd>method</kbd> `Api.create_automation`

```python
create_automation(
    obj: 'NewAutomation',
    fetch_existing: bool = False,
    **kwargs: typing_extensions.Unpack[ForwardRef('WriteAutomationsKwargs')]
) → Automation

Create a new Automation.

Args: obj: The automation to create. fetch_existing: If True, and a conflicting automation already exists, attempt to fetch the existing automation instead of raising an error. **kwargs: Any additional values to assign to the automation before creating it. If given, these will override any values that may already be set on the automation: - name: The name of the automation. - description: The description of the automation. - enabled: Whether the automation is enabled. - scope: The scope of the automation. - event: The event that triggers the automation. - action: The action that is triggered by the automation.

Returns: The saved Automation.

Examples: Create a new automation named “my-automation” that sends a Slack notification when a run within a specific project logs a metric exceeding a custom threshold:

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

     api = wandb.Api()

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

     # Use the first Slack integration for the team
     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.",
     )
    ``` 

---

### <kbd>method</kbd> `Api.create_project`

```python
create_project(name: str, entity: str) → None

Create a new project.

Args:

• name: The name of the new project.
• entity: The entity of the new project.

method Api.create_registry

create_registry(
    name: str,
    visibility: Literal['organization', 'restricted'],
    organization: Optional[str] = None,
    description: Optional[str] = None,
    artifact_types: Optional[List[str]] = None
) → Registry

Create a new registry.

Args:

• name: The name of the registry. Name must be unique within the organization.
• visibility: The visibility of the registry.
• organization: Anyone in the organization can view this registry. You can edit their roles later from the settings in the UI.
• restricted: Only invited members via the UI can access this registry. Public sharing is disabled.
• organization: The organization of the registry. If no organization is set in the settings, the organization will be fetched from the entity if the entity only belongs to one organization.
• description: The description of the registry.
• artifact_types: The accepted artifact types of the registry. A type is no
• more than 128 characters and do not include characters /or ``:. If not specified, all types are accepted. Allowed types added to the registry cannot be removed later.

Returns: A registry object.

Examples:

   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"],
   )
   ``` 

---

### <kbd>method</kbd> `Api.create_run`

```python
create_run(
   run_id: Optional[str] = None,
   project: Optional[str] = None,
   entity: Optional[str] = None
) → public.Run

Create a new run.

Args:

• run_id: The ID to assign to the run. If not specified, W&B creates a random ID.
• project: The project where to log the run to. If no project is specified, log the run to a project called “Uncategorized”.
• entity: The entity that owns the project. If no entity is specified, log the run to the default entity.

Returns: The newly created Run.

method Api.create_run_queue

create_run_queue(
    name: str,
    type: 'public.RunQueueResourceType',
    entity: Optional[str] = None,
    prioritization_mode: Optional[ForwardRef('public.RunQueuePrioritizationMode')] = None,
    config: Optional[dict] = None,
    template_variables: Optional[dict] = None
) → public.RunQueue

Create a new run queue in W&B Launch.

Args:

• name: Name of the queue to create
• type: Type of resource to be used for the queue. One of “local-container”, “local-process”, “kubernetes”,“sagemaker”, or “gcp-vertex”.
• entity: Name of the entity to create the queue. If None, use the configured or default entity.
• prioritization_mode: Version of prioritization to use. Either “V0” or None.
• config: Default resource configuration to be used for the queue. Use handlebars (eg. {{var}}) to specify template variables.
• template_variables: A dictionary of template variable schemas to use with the config.

Returns: The newly created RunQueue.

Raises: ValueError if any of the parameters are invalid wandb.Error on wandb API errors

method Api.create_team

create_team(team: str, admin_username: Optional[str] = None) → public.Team

Create a new team.

Args:

• team: The name of the team
• admin_username: Username of the admin user of the team. Defaults to the current user.

Returns: A Team object.

method Api.create_user

create_user(email: str, admin: Optional[bool] = False)

Create a new user.

Args:

• email: The email address of the user.
• admin: Set user as a global instance administrator.

Returns: A User object.

method Api.delete_automation

delete_automation(obj: Union[ForwardRef('Automation'), str]) → Literal[True]

Delete an automation.

Args:

• obj: The automation to delete, or its ID.

Returns: True if the automation was deleted successfully.

method Api.flush

flush()

Flush the local cache.

The api object keeps a local cache of runs, so if the state of the run may change while executing your script you must clear the local cache with api.flush() to get the latest values associated with the run.

method Api.from_path

from_path(path: str)

Return a run, sweep, project or report from a path.

Args:

• path: The path to the project, run, sweep or report

Returns: A Project, Run, Sweep, or BetaReport instance.

Raises: wandb.Error if path is invalid or the object doesn’t exist.

Examples: In the proceeding code snippets “project”, “team”, “run_id”, “sweep_id”, and “report_name” are placeholders for the project, team, run ID, sweep ID, and the name of a specific report, respectively.

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")

method Api.integrations

integrations(
    entity: Optional[str] = None,
    per_page: int = 50
) → Iterator[ForwardRef('Integration')]

Return an iterator of all integrations for an entity.

Args:

• entity: The entity (e.g. team name) for which to fetch integrations. If not provided, the user’s default entity will be used.
• per_page: Number of integrations to fetch per page. Defaults to 50. Usually there is no reason to change this.

Yields:

• Iterator[SlackIntegration | WebhookIntegration]: An iterator of any supported integrations.

method Api.job

job(name: Optional[str], path: Optional[str] = None) → public.Job

Return a Job object.

Args:

• name: The name of the job.
• path: The root path to download the job artifact.

Returns: A Job object.

method Api.list_jobs

list_jobs(entity: str, project: str) → List[Dict[str, Any]]

Return a list of jobs, if any, for the given entity and project.

Args:

• entity: The entity for the listed jobs.
• project: The project for the listed jobs.

Returns: A list of matching jobs.

method Api.project

project(name: str, entity: Optional[str] = None) → public.Project

Return the Project with the given name (and entity, if given).

Args:

• name: The project name.
• entity: Name of the entity requested. If None, will fall back to the default entity passed to Api. If no default entity, will raise a ValueError.

Returns: A Project object.

method Api.projects

projects(entity: Optional[str] = None, per_page: int = 200) → public.Projects

Get projects for a given entity.

Args:

• entity: Name of the entity requested. If None, will fall back to the default entity passed to Api. If no default entity, will raise a ValueError.
• per_page: Sets the page size for query pagination. If set to None, use the default size. Usually there is no reason to change this.

Returns: A Projects object which is an iterable collection of Projectobjects.

method Api.queued_run

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

Return a single queued run based on the path.

Parses paths of the form entity/project/queue_id/run_queue_item_id.

method Api.registries

registries(
    organization: Optional[str] = None,
    filter: Optional[Dict[str, Any]] = None
) → Registries

Returns a Registry iterator.

Use the iterator to search and filter registries, collections, or artifact versions across your organization’s registry.

Examples: Find all registries with the names that contain “model” ```python import wandb

 api = wandb.Api()  # specify an org if your entity belongs to multiple orgs
 api.registries(filter={"name": {"$regex": "model"}})
``` 

Find all collections in the registries with the name “my_collection” and the tag “my_tag” python api.registries().collections(filter={"name": "my_collection", "tag": "my_tag"})

Find all artifact versions in the registries with a collection name that contains “my_collection” and a version that has the alias “best” python api.registries().collections( filter={"name": {"$regex": "my_collection"}} ).versions(filter={"alias": "best"})

Find all artifact versions in the registries that contain “model” and have the tag “prod” or alias “best” python api.registries(filter={"name": {"$regex": "model"}}).versions( filter={"$or": [{"tag": "prod"}, {"alias": "best"}]} )

Args:

• organization: (str, optional) The organization of the registry to fetch. If not specified, use the organization specified in the user’s settings.
• filter: (dict, optional) MongoDB-style filter to apply to each object in the registry iterator. Fields available to filter for collections are name, description, created_at, updated_at. Fields available to filter for collections are name, tag, description, created_at, updated_at Fields available to filter for versions are tag, alias, created_at, updated_at, metadata

Returns: A registry iterator.

method Api.registry

registry(name: str, organization: Optional[str] = None) → Registry

Return a registry given a registry name.

Args:

• name: The name of the registry. This is without the wandb-registry- prefix.
• organization: The organization of the registry. If no organization is set in the settings, the organization will be fetched from the entity if the entity only belongs to one organization.

Returns: A registry object.

Examples: Fetch and update a registry ```python import wandb

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

method Api.reports

reports(
    path: str = '',
    name: Optional[str] = None,
    per_page: int = 50
) → public.Reports

Get reports for a given project path.

Note: wandb.Api.reports() API is in beta and will likely change in future releases.

Args:

• path: The path to project the report resides in. Specify the entity that created the project as a prefix followed by a forward slash.
• name: Name of the report requested.
• per_page: Sets the page size for query pagination. If set to None, use the default size. Usually there is no reason to change this.

Returns: A Reports object which is an iterable collection of BetaReport objects.

Examples:

import wandb

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

method Api.run

run(path='')

Return a single run by parsing path in the form entity/project/run_id.

Args:

• path: Path to run in the form entity/project/run_id. If api.entity is set, this can be in the form project/run_id and if api.project is set this can just be the run_id.

Returns: A Run object.

method Api.run_queue

run_queue(entity: str, name: str)

Return the named RunQueue for entity.

See Api.create_run_queue for more information on how to create a run queue.

method Api.runs

runs(
    path: Optional[str] = None,
    filters: Optional[Dict[str, Any]] = None,
    order: str = '+created_at',
    per_page: int = 50,
    include_sweeps: bool = True
)

Return a set of runs from a project that match the filters provided.

Fields you can filter by include:

• createdAt: The timestamp when the run was created. (in ISO 8601 format, e.g. “2023-01-01T12:00:00Z”)
• displayName: The human-readable display name of the run. (e.g. “eager-fox-1”)
• duration: The total runtime of the run in seconds.
• group: The group name used to organize related runs together.
• host: The hostname where the run was executed.
• jobType: The type of job or purpose of the run.
• name: The unique identifier of the run. (e.g. “a1b2cdef”)
• state: The current state of the run.
• tags: The tags associated with the run.
• username: The username of the user who initiated the run

Additionally, you can filter by items in the run config or summary metrics. Such as config.experiment_name, summary_metrics.loss, etc.

For more complex filtering, you can use MongoDB query operators. For details, see: https://docs.mongodb.com/manual/reference/operator/query The following operations are supported:

• $and
• $or
• $nor
• $eq
• $ne
• $gt
• $gte
• $lt
• $lte
• $in
• $nin
• $exists
• $regex

Args:

• path: (str) path to project, should be in the form: “entity/project”
• filters: (dict) queries for specific runs using the MongoDB query language. You can filter by run properties such as config.key, summary_metrics.key, state, entity, createdAt, etc.
• For example: {"config.experiment_name": "foo"} would find runs with a config entry of experiment name set to “foo”
• order: (str) Order can be created_at, heartbeat_at, config.*.value, or summary_metrics.*. If you prepend order with a + order is ascending. If you prepend order with a - order is descending (default). The default order is run.created_at from oldest to newest.
• per_page: (int) Sets the page size for query pagination.
• include_sweeps: (bool) Whether to include the sweep runs in the results.

Returns: A Runs object, which is an iterable collection of Run objects.

Examples:

# Find runs in project where config.experiment_name has been set to "foo"
api.runs(path="my_entity/project", filters={"config.experiment_name": "foo"})

# Find runs in project where config.experiment_name has been set to "foo" or "bar"
api.runs(
    path="my_entity/project",
    filters={
         "$or": [
             {"config.experiment_name": "foo"},
             {"config.experiment_name": "bar"},
         ]
    },
)

# Find runs in project where config.experiment_name matches a regex
# (anchors are not supported)
api.runs(
    path="my_entity/project",
    filters={"config.experiment_name": {"$regex": "b.*"}},
)

# Find runs in project where the run name matches a regex
# (anchors are not supported)
api.runs(
    path="my_entity/project", filters={"display_name": {"$regex": "^foo.*"}}
)

# Find runs in project sorted by ascending loss
api.runs(path="my_entity/project", order="+summary_metrics.loss")

method Api.slack_integrations

slack_integrations(
    entity: Optional[str] = None,
    per_page: int = 50
) → Iterator[ForwardRef('SlackIntegration')]

Returns an iterator of Slack integrations for an entity.

Args:

• entity: The entity (e.g. team name) for which to fetch integrations. If not provided, the user’s default entity will be used.
• per_page: Number of integrations to fetch per page. Defaults to 50. Usually there is no reason to change this.

Yields:

• Iterator[SlackIntegration]: An iterator of Slack integrations.

Examples: Get all registered Slack integrations for the team “my-team”: ```python import wandb

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

Find only Slack integrations that post to channel names starting with “team-alerts-”: python slack_integrations = api.slack_integrations(entity="my-team") team_alert_integrations = [ ig for ig in slack_integrations if ig.channel_name.startswith("team-alerts-") ]

method Api.sweep

sweep(path='')

Return a sweep by parsing path in the form entity/project/sweep_id.

Args:

• path: Path to sweep in the form entity/project/sweep_id. If api.entity is set, this can be in the form project/sweep_id and if api.project is set this can just be the sweep_id.

Returns: A Sweep object.

method Api.sync_tensorboard

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

Sync a local directory containing tfevent files to wandb.

method Api.team

team(team: str) → public.Team

Return the matching Team with the given name.

Args:

• team: The name of the team.

Returns: A Team object.

method Api.update_automation

update_automation(
    obj: 'Automation',
    create_missing: bool = False,
    **kwargs: typing_extensions.Unpack[ForwardRef('WriteAutomationsKwargs')]
) → Automation

Update an existing automation.

Args:

• obj: The automation to update. Must be an existing automation. create_missing (bool): If True, and the automation does not exist, create it. **kwargs: Any additional values to assign to the automation before updating it. If given, these will override any values that may already be set on the automation: - name: The name of the automation. - description: The description of the automation. - enabled: Whether the automation is enabled. - scope: The scope of the automation. - event: The event that triggers the automation. - action: The action that is triggered by the automation.

Returns: The updated automation.

Examples: Disable and edit the description of an existing automation (“my-automation”):

    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)
    ``` 

OR: 

```python
    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.",
    )
    ``` 

---

### <kbd>method</kbd> `Api.upsert_run_queue`

```python
upsert_run_queue(
    name: str,
    resource_config: dict,
    resource_type: 'public.RunQueueResourceType',
    entity: Optional[str] = None,
    template_variables: Optional[dict] = None,
    external_links: Optional[dict] = None,
    prioritization_mode: Optional[ForwardRef('public.RunQueuePrioritizationMode')] = None
)

Upsert a run queue in W&B Launch.

Args:

• name: Name of the queue to create
• entity: Optional name of the entity to create the queue. If None, use the configured or default entity.
• resource_config: Optional default resource configuration to be used for the queue. Use handlebars (eg. {{var}}) to specify template variables.
• resource_type: Type of resource to be used for the queue. One of “local-container”, “local-process”, “kubernetes”, “sagemaker”, or “gcp-vertex”.
• template_variables: A dictionary of template variable schemas to be used with the config.
• external_links: Optional dictionary of external links to be used with the queue.
• prioritization_mode: Optional version of prioritization to use. Either “V0” or None

Returns: The upserted RunQueue.

Raises: ValueError if any of the parameters are invalid wandb.Error on wandb API errors

method Api.user

user(username_or_email: str) → Optional[ForwardRef('public.User')]

Return a user from a username or email address.

This function only works for local administrators. Use api.viewer to get your own user object.

Args:

• username_or_email: The username or email address of the user.

Returns: A User object or None if a user is not found.

method Api.users

users(username_or_email: str) → List[ForwardRef('public.User')]

Return all users from a partial username or email address query.

This function only works for local administrators. Use api.viewer to get your own user object.

Args:

• username_or_email: The prefix or suffix of the user you want to find.

Returns: An array of User objects.

method Api.webhook_integrations

webhook_integrations(
    entity: Optional[str] = None,
    per_page: int = 50
) → Iterator[ForwardRef('WebhookIntegration')]

Returns an iterator of webhook integrations for an entity.

Args:

• entity: The entity (e.g. team name) for which to fetch integrations. If not provided, the user’s default entity will be used.
• per_page: Number of integrations to fetch per page. Defaults to 50. Usually there is no reason to change this.

Yields:

• Iterator[WebhookIntegration]: An iterator of webhook integrations.

Examples: Get all registered webhook integrations for the team “my-team”: ```python import wandb

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

Find only webhook integrations that post requests to “https://my-fake-url.com”: python 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") ]

2 - artifacts

module wandb.apis.public

W&B Public API for Artifact objects.

This module provides classes for interacting with W&B artifacts and their collections.

function server_supports_artifact_collections_gql_edges

server_supports_artifact_collections_gql_edges(
    client: 'RetryingClient',
    warn: 'bool' = False
) → bool

Check if W&B server supports GraphQL edges for artifact collections.

class ArtifactTypes

method ArtifactTypes.__init__

__init__(client: 'Client', entity: 'str', project: 'str', per_page: 'int' = 50)

property ArtifactTypes.cursor

Returns the cursor for the next page of results.

property ArtifactTypes.length

Returns None.

property ArtifactTypes.more

Returns whether there are more artifact types to fetch.

method ArtifactTypes.convert_objects

convert_objects() → list[ArtifactType]

Convert the raw response data into a list of ArtifactType objects.

method ArtifactTypes.update_variables

update_variables() → None

Update the cursor variable for pagination.

class ArtifactType

An artifact object that satisfies query based on the specified type.

Args:

• client: The client instance to use for querying W&B.
• entity: The entity (user or team) that owns the project.
• project: The name of the project to query for artifact types.
• type_name: The name of the artifact type.
• attrs: Optional mapping of attributes to initialize the artifact type. If not provided, the object will load its attributes from W&B upon initialization.

method ArtifactType.__init__

__init__(
    client: 'Client',
    entity: 'str',
    project: 'str',
    type_name: 'str',
    attrs: 'Mapping[str, Any] | None' = None
)

property ArtifactType.id

The unique identifier of the artifact type.

property ArtifactType.name

The name of the artifact type.

method ArtifactType.collection

collection(name: 'str') → ArtifactCollection

Get a specific artifact collection by name.

Args:

• name (str): The name of the artifact collection to retrieve.

method ArtifactType.collections

collections(per_page: 'int' = 50) → ArtifactCollections

Get all artifact collections associated with this artifact type.

Args:

• per_page (int): The number of artifact collections to fetch per page. Default is 50.

method ArtifactType.load

load() → Mapping[str, Any]

Load the artifact type attributes from W&B.

class ArtifactCollections

Artifact collections of a specific type in a project.

Args:

• client: The client instance to use for querying W&B.
• entity: The entity (user or team) that owns the project.
• project: The name of the project to query for artifact collections.
• type_name: The name of the artifact type for which to fetch collections.
• per_page: The number of artifact collections to fetch per page. Default is 50.

method ArtifactCollections.__init__

__init__(
    client: 'Client',
    entity: 'str',
    project: 'str',
    type_name: 'str',
    per_page: 'int' = 50
)

property ArtifactCollections.cursor

Returns the cursor for the next page of results.

property ArtifactCollections.length

property ArtifactCollections.more

Returns whether there are more artifacts to fetch.

method ArtifactCollections.convert_objects

convert_objects() → list[ArtifactCollection]

Convert the raw response data into a list of ArtifactCollection objects.

method ArtifactCollections.update_variables

update_variables() → None

Update the cursor variable for pagination.

class ArtifactCollection

An artifact collection that represents a group of related artifacts.

Args:

• client: The client instance to use for querying W&B.
• entity: The entity (user or team) that owns the project.
• project: The name of the project to query for artifact collections.
• name: The name of the artifact collection.
• type: The type of the artifact collection (e.g., “dataset”, “model”).
• organization: Optional organization name if applicable.
• attrs: Optional mapping of attributes to initialize the artifact collection. If not provided, the object will load its attributes from W&B upon initialization.

method ArtifactCollection.__init__

__init__(
    client: 'Client',
    entity: 'str',
    project: 'str',
    name: 'str',
    type: 'str',
    organization: 'str | None' = None,
    attrs: 'Mapping[str, Any] | None' = None,
    is_sequence: 'bool | None' = None
)

property ArtifactCollection.aliases

Artifact Collection Aliases.

property ArtifactCollection.created_at

The creation date of the artifact collection.

property ArtifactCollection.description

A description of the artifact collection.

property ArtifactCollection.id

The unique identifier of the artifact collection.

property ArtifactCollection.name

The name of the artifact collection.

property ArtifactCollection.tags

The tags associated with the artifact collection.

property ArtifactCollection.type

Returns the type of the artifact collection.

method ArtifactCollection.artifacts

artifacts(per_page: 'int' = 50) → Artifacts

Get all artifacts in the collection.

method ArtifactCollection.change_type

change_type(new_type: 'str') → None

Deprecated, change type directly with save instead.

method ArtifactCollection.delete

delete() → None

Delete the entire artifact collection.

method ArtifactCollection.is_sequence

is_sequence() → bool

Return whether the artifact collection is a sequence.

method ArtifactCollection.load

load()

Load the artifact collection attributes from W&B.

method ArtifactCollection.save

save() → None

Persist any changes made to the artifact collection.

class Artifacts

An iterable collection of artifact versions associated with a project.

Optionally pass in filters to narrow down the results based on specific criteria.

Args:

• client: The client instance to use for querying W&B.
• entity: The entity (user or team) that owns the project.
• project: The name of the project to query for artifacts.
• collection_name: The name of the artifact collection to query.
• type: The type of the artifacts to query. Common examples include “dataset” or “model”.
• filters: Optional mapping of filters to apply to the query.
• order: Optional string to specify the order of the results.
• per_page: The number of artifact versions to fetch per page. Default is 50.
• tags: Optional string or list of strings to filter artifacts by tags.

method Artifacts.__init__

__init__(
    client: 'Client',
    entity: 'str',
    project: 'str',
    collection_name: 'str',
    type: 'str',
    filters: 'Mapping[str, Any] | None' = None,
    order: 'str | None' = None,
    per_page: 'int' = 50,
    tags: 'str | list[str] | None' = None
)

property Artifacts.cursor

Returns the cursor for the next page of results.

property Artifacts.length

Returns the total number of artifacts in the collection.

property Artifacts.more

Returns whether there are more files to fetch.

method Artifacts.convert_objects

convert_objects() → list[Artifact]

Convert the raw response data into a list of wandb.Artifact objects.

class RunArtifacts

method RunArtifacts.__init__

__init__(
    client: 'Client',
    run: 'Run',
    mode: "Literal['logged', 'used']" = 'logged',
    per_page: 'int' = 50
)

property RunArtifacts.cursor

Returns the cursor for the next page of results.

property RunArtifacts.length

Returns the total number of artifacts in the collection.

property RunArtifacts.more

Returns whether there are more artifacts to fetch.

method RunArtifacts.convert_objects

convert_objects() → list[Artifact]

Convert the raw response data into a list of wandb.Artifact objects.

class ArtifactFiles

method ArtifactFiles.__init__

__init__(
    client: 'Client',
    artifact: 'Artifact',
    names: 'Sequence[str] | None' = None,
    per_page: 'int' = 50
)

property ArtifactFiles.cursor

Returns the cursor for the next page of results.

property ArtifactFiles.length

Returns the total number of files in the artifact.

property ArtifactFiles.more

Returns whether there are more files to fetch.

property ArtifactFiles.path

Returns the path of the artifact.

method ArtifactFiles.convert_objects

convert_objects() → list[public.File]

Convert the raw response data into a list of public.File objects.

method ArtifactFiles.update_variables

update_variables() → None

Update the variables dictionary with the cursor.

3 - automations

module wandb.apis.public

W&B Public API for Automation objects.

class Automations

An iterable collection of Automation objects.

method Automations.__init__

__init__(
    client: '_Client',
    variables: 'Mapping[str, Any]',
    per_page: 'int' = 50,
    _query: 'Document | None' = None
)

property Automations.cursor

The start cursor to use for the next page.

property Automations.more

Whether there are more items to fetch.

method Automations.convert_objects

convert_objects() → Iterable[Automation]

Parse the page data into a list of objects.

4 - files

module wandb.apis.public

W&B Public API for File objects.

This module provides classes for interacting with files stored in W&B.

Example:

from wandb.apis.public import Api

# Initialize API
api = Api()

# Get files from a specific run
run = api.run("entity/project/run_id")
files = run.files()

# Work with files
for file in files:
    print(f"File: {file.name}")
    print(f"Size: {file.size} bytes")
    print(f"Type: {file.mimetype}")

    # Download file
    if file.size < 1000000:  # Less than 1MB
        file.download(root="./downloads")

    # Get S3 URI for large files
    if file.size >= 1000000:
        print(f"S3 URI: {file.path_uri}")

Note:

This module is part of the W&B Public API and provides methods to access, download, and manage files stored in W&B. Files are typically associated with specific runs and can include model weights, datasets, visualizations, and other artifacts.

class Files

An iterable collection of File objects.

Access and manage files uploaded to W&B during a run. Handles pagination automatically when iterating through large collections of files.

Args:

• client: The run object that contains the files
• run: The run object that contains the files
• names (list, optional): A list of file names to filter the files
• per_page (int, optional): The number of files to fetch per page
• upload (bool, optional): If True, fetch the upload URL for each file

Example:

from wandb.apis.public.files import Files
from wandb.apis.public.api import Api

# Initialize the API client
api = Api()

# Example run object
run = api.run("entity/project/run-id")

# Create a Files object to iterate over files in the run
files = Files(api.client, run)

# Iterate over files
for file in files:
   print(file.name)
   print(file.url)
   print(file.size)

   # Download the file
   file.download(root="download_directory", replace=True)

method Files.__init__

__init__(client, run, names=None, per_page=50, upload=False)

property Files.cursor

Returns the cursor position for pagination of file results.

property Files.length

The number of files saved to the specified run.

property Files.more

Returns whether there are more files to fetch.

method Files.convert_objects

convert_objects()

Converts GraphQL edges to File objects.

method Files.update_variables

update_variables()

Updates the GraphQL query variables for pagination.

class File

File saved to W&B.

Represents a single file stored in W&B. Includes access to file metadata. Files are associated with a specific run and can include text files, model weights, datasets, visualizations, and other artifacts. You can download the file, delete the file, and access file properties.

Specify one or more attributes in a dictionary to fine a specific file logged to a specific run. You can search using the following keys:

• id (str): The ID of the run that contains the file
• name (str): Name of the file
• url (str): path to file
• direct_url (str): path to file in the bucket
• sizeBytes (int): size of file in bytes
• md5 (str): md5 of file
• mimetype (str): mimetype of file
• updated_at (str): timestamp of last update
• path_uri (str): path to file in the bucket, currently only available for files stored in S3

Args:

• client: The run object that contains the file
• attrs (dict): A dictionary of attributes that define the file
• run: The run object that contains the file

Example:

from wandb.apis.public.files import File
from wandb.apis.public.api import Api

# Initialize the API client
api = Api()

# Example attributes dictionary
file_attrs = {
   "id": "file-id",
   "name": "example_file.txt",
   "url": "https://example.com/file",
   "direct_url": "https://example.com/direct_file",
   "sizeBytes": 1024,
   "mimetype": "text/plain",
   "updated_at": "2025-03-25T21:43:51Z",
   "md5": "d41d8cd98f00b204e9800998ecf8427e",
}

# Example run object
run = api.run("entity/project/run-id")

# Create a File object
file = File(api.client, file_attrs, run)

# Access some of the attributes
print("File ID:", file.id)
print("File Name:", file.name)
print("File URL:", file.url)
print("File MIME Type:", file.mimetype)
print("File Updated At:", file.updated_at)

# Access File properties
print("File Size:", file.size)
print("File Path URI:", file.path_uri)

# Download the file
file.download(root="download_directory", replace=True)

# Delete the file
file.delete()

method File.__init__

__init__(client, attrs, run=None)

property File.path_uri

Returns the URI path to the file in the storage bucket.

property File.size

Returns the size of the file in bytes.

method File.delete

delete()

Delete the file from the W&B server.

method File.download

download(
    root: str = '.',
    replace: bool = False,
    exist_ok: bool = False,
    api: Optional[wandb.apis.public.api.Api] = None
) → TextIOWrapper

Downloads a file previously saved by a run from the wandb server.

Args:

• root: Local directory to save the file. Defaults to “.”.
• replace: If True, download will overwrite a local file if it exists. Defaults to False.
• exist_ok: If True, will not raise ValueError if file already exists and will not re-download unless replace=True. Defaults to False.
• api: If specified, the Api instance used to download the file.

Raises: ValueError if file already exists, replace=False and exist_ok=False.

5 - history

module wandb.apis.public

W&B Public API for Run History.

This module provides classes for efficiently scanning and sampling run history data.

Note:

This module is part of the W&B Public API and provides methods to access run history data. It handles pagination automatically and offers both complete and sampled access to metrics logged during training runs.

class HistoryScan

Iterator for scanning complete run history.

Args:

• client: (wandb.apis.internal.Api) The client instance to use
• run: (wandb.sdk.internal.Run) The run object to scan history for
• min_step: (int) The minimum step to start scanning from
• max_step: (int) The maximum step to scan up to
• page_size: (int) Number of samples per page (default is 1000)

method HistoryScan.__init__

__init__(client, run, min_step, max_step, page_size=1000)

class SampledHistoryScan

Iterator for sampling run history data.

Args:

• client: (wandb.apis.internal.Api) The client instance to use
• run: (wandb.sdk.internal.Run) The run object to sample history from
• keys: (list) List of keys to sample from the history
• min_step: (int) The minimum step to start sampling from
• max_step: (int) The maximum step to sample up to
• page_size: (int) Number of samples per page (default is 1000)

method SampledHistoryScan.__init__

__init__(client, run, keys, min_step, max_step, page_size=1000)

6 - integrations

module wandb.apis.public

W&B Public API for integrations.

This module provides classes for interacting with W&B integrations.

class Integrations

method Integrations.__init__

__init__(client: '_Client', variables: 'dict[str, Any]', per_page: 'int' = 50)

property Integrations.cursor

The start cursor to use for the next page.

property Integrations.more

Whether there are more Integrations to fetch.

method Integrations.convert_objects

convert_objects() → Iterable[Integration]

Parse the page data into a list of integrations.

class WebhookIntegrations

method WebhookIntegrations.__init__

__init__(client: '_Client', variables: 'dict[str, Any]', per_page: 'int' = 50)

property WebhookIntegrations.cursor

The start cursor to use for the next page.

property WebhookIntegrations.more

Whether there are more webhook integrations to fetch.

method WebhookIntegrations.convert_objects

convert_objects() → Iterable[WebhookIntegration]

Parse the page data into a list of webhook integrations.

class SlackIntegrations

method SlackIntegrations.__init__

__init__(client: '_Client', variables: 'dict[str, Any]', per_page: 'int' = 50)

property SlackIntegrations.cursor

The start cursor to use for the next page.

property SlackIntegrations.more

Whether there are more Slack integrations to fetch.

method SlackIntegrations.convert_objects

convert_objects() → Iterable[SlackIntegration]

Parse the page data into a list of Slack integrations.

7 - jobs

module wandb.apis.public

W&B Public API for management Launch Jobs and Launch Queues.

This module provides classes for managing W&B jobs, queued runs, and run queues.

class Job

method Job.__init__

__init__(api: 'Api', name, path: Optional[str] = None) → None

property Job.name

The name of the job.

method Job.call

call(
    config,
    project=None,
    entity=None,
    queue=None,
    resource='local-container',
    resource_args=None,
    template_variables=None,
    project_queue=None,
    priority=None
)

Call the job with the given configuration.

Args:

• config (dict): The configuration to pass to the job. This should be a dictionary containing key-value pairs that match the input types defined in the job.
• project (str, optional): The project to log the run to. Defaults to the job’s project.
• entity (str, optional): The entity to log the run under. Defaults to the job’s entity.
• queue (str, optional): The name of the queue to enqueue the job to. Defaults to None.
• resource (str, optional): The resource type to use for execution. Defaults to “local-container”.
• resource_args (dict, optional): Additional arguments for the resource type. Defaults to None.
• template_variables (dict, optional): Template variables to use for the job. Defaults to None.
• project_queue (str, optional): The project that manages the queue. Defaults to None.
• priority (int, optional): The priority of the queued run. Defaults to None.

method Job.set_entrypoint

set_entrypoint(entrypoint: List[str])

Set the entrypoint for the job.

class QueuedRun

A single queued run associated with an entity and project.

Args:

• entity: The entity associated with the queued run.
• project (str): The project where runs executed by the queue are logged to.
• queue_name (str): The name of the queue.
• run_queue_item_id (int): The id of the run queue item.
• project_queue (str): The project that manages the queue.
• priority (str): The priority of the queued run.

Call run = queued_run.wait_until_running() or run = queued_run.wait_until_finished() to access the run.

method QueuedRun.__init__

__init__(
    client,
    entity,
    project,
    queue_name,
    run_queue_item_id,
    project_queue='model-registry',
    priority=None
)

property QueuedRun.entity

The entity associated with the queued run.

property QueuedRun.id

The id of the queued run.

property QueuedRun.project

The project associated with the queued run.

property QueuedRun.queue_name

The name of the queue.

property QueuedRun.state

The state of the queued run.

method QueuedRun.delete

delete(delete_artifacts=False)

Delete the given queued run from the wandb backend.

method QueuedRun.wait_until_finished

wait_until_finished()

Wait for the queued run to complete and return the finished run.

method QueuedRun.wait_until_running

wait_until_running()

Wait until the queued run is running and return the run.

class RunQueue

Class that represents a run queue in W&B.

Args:

• client: W&B API client instance.
• name: Name of the run queue
• entity: The entity (user or team) that owns this queue
• prioritization_mode: Queue priority mode Can be “DISABLED” or “V0”. Defaults to None.
• _access: Access level for the queue Can be “project” or “user”. Defaults to None.
• _default_resource_config_id: ID of default resource config
• _default_resource_config: Default resource configuration

method RunQueue.__init__

__init__(
    client: 'RetryingClient',
    name: str,
    entity: str,
    prioritization_mode: Optional[Literal['DISABLED', 'V0']] = None,
    _access: Optional[Literal['project', 'user']] = None,
    _default_resource_config_id: Optional[int] = None,
    _default_resource_config: Optional[dict] = None
) → None

property RunQueue.access

The access level of the queue.

property RunQueue.default_resource_config

The default configuration for resources.

property RunQueue.entity

The entity that owns the queue.

property RunQueue.external_links

External resource links for the queue.

property RunQueue.id

The id of the queue.

property RunQueue.items

Up to the first 100 queued runs. Modifying this list will not modify the queue or any enqueued items!

property RunQueue.name

The name of the queue.

property RunQueue.prioritization_mode

The prioritization mode of the queue.

Can be set to “DISABLED” or “V0”.

property RunQueue.template_variables

Variables for resource templates.

property RunQueue.type

The resource type for execution.

classmethod RunQueue.create

create(
    name: str,
    resource: 'RunQueueResourceType',
    entity: Optional[str] = None,
    prioritization_mode: Optional[ForwardRef('RunQueuePrioritizationMode')] = None,
    config: Optional[dict] = None,
    template_variables: Optional[dict] = None
) → RunQueue

Create a RunQueue.

Args:

• name: The name of the run queue to create.
• resource: The resource type for execution.
• entity: The entity (user or team) that will own the queue. Defaults to the default entity of the API client.
• prioritization_mode: The prioritization mode for the queue. Can be “DISABLED” or “V0”. Defaults to None.
• config: Optional dictionary for the default resource configuration. Defaults to None.
• template_variables: Optional dictionary for template variables used in the resource configuration.

method RunQueue.delete

delete()

Delete the run queue from the wandb backend.

8 - projects

module wandb.apis.public

W&B Public API for Project objects.

This module provides classes for interacting with W&B projects and their associated data.

Example:

from wandb.apis.public import Api

# Initialize API
api = Api()

# Get all projects for an entity
projects = api.projects("entity")

# Access project data
for project in projects:
    print(f"Project: {project.name}")
    print(f"URL: {project.url}")

    # Get artifact types
    for artifact_type in project.artifacts_types():
        print(f"Artifact Type: {artifact_type.name}")

    # Get sweeps
    for sweep in project.sweeps():
        print(f"Sweep ID: {sweep.id}")
        print(f"State: {sweep.state}")

Note:

This module is part of the W&B Public API and provides methods to access and manage projects. For creating new projects, use wandb.init() with a new project name.

class Projects

An iterable collection of Project objects.

An iterable interface to access projects created and saved by the entity.

Args:

• client (wandb.apis.internal.Api): The API client instance to use.
• entity (str): The entity name (username or team) to fetch projects for.
• per_page (int): Number of projects to fetch per request (default is 50).

Example:

from wandb.apis.public.api import Api

# Initialize the API client
api = Api()

# Find projects that belong to this entity
projects = api.projects(entity="entity")

# Iterate over files
for project in projects:
   print(f"Project: {project.name}")
   print(f"- URL: {project.url}")
   print(f"- Created at: {project.created_at}")
   print(f"- Is benchmark: {project.is_benchmark}")

method Projects.__init__

__init__(client, entity, per_page=50)

property Projects.cursor

Returns the cursor position for pagination of project results.

property Projects.length

Returns the total number of projects.

Note: This property is not available for projects.

property Projects.more

Returns True if there are more projects to fetch. Returns False if there are no more projects to fetch.

method Projects.convert_objects

convert_objects()

Converts GraphQL edges to File objects.

class Project

A project is a namespace for runs.

Args:

• client: W&B API client instance.
• name (str): The name of the project.
• entity (str): The entity name that owns the project.

method Project.__init__

__init__(client, entity, project, attrs)

property Project.id

property Project.path

Returns the path of the project. The path is a list containing the entity and project name.

property Project.url

Returns the URL of the project.

method Project.artifacts_types

artifacts_types(per_page=50)

Returns all artifact types associated with this project.

method Project.sweeps

sweeps()

Fetches all sweeps associated with the project.

9 - query_generator

module wandb.apis.public

method QueryGenerator.filter_to_mongo

filter_to_mongo(filter)

Returns dictionary with filter format converted to MongoDB filter.

classmethod QueryGenerator.format_order_key

format_order_key(key: str)

Format a key for sorting.

method QueryGenerator.key_to_server_path

key_to_server_path(key)

Convert a key dictionary to the corresponding server path string.

method QueryGenerator.keys_to_order

keys_to_order(keys)

Convert a list of key dictionaries to an order string.

method QueryGenerator.mongo_to_filter

mongo_to_filter(filter)

Returns dictionary with MongoDB filter converted to filter format.

method QueryGenerator.order_to_keys

order_to_keys(order)

Convert an order string to a list of key dictionaries.

method QueryGenerator.server_path_to_key

server_path_to_key(path)

Convert a server path string to the corresponding key dictionary.

10 - reports

module wandb.apis.public

W&B Public API for Report objects.

This module provides classes for interacting with W&B reports and managing report-related data.

class Reports

Reports is an iterable collection of BetaReport objects.

Args:

• client (wandb.apis.internal.Api): The API client instance to use.
• project (wandb.sdk.internal.Project): The project to fetch reports from.
• name (str, optional): The name of the report to filter by. If None, fetches all reports.
• entity (str, optional): The entity name for the project. Defaults to the project entity.
• per_page (int): Number of reports to fetch per page (default is 50).

method Reports.__init__

__init__(client, project, name=None, entity=None, per_page=50)

property Reports.cursor

Returns the cursor position for pagination of file results.

property Reports.length

The number of reports in the project.

property Reports.more

Returns whether there are more files to fetch.

method Reports.convert_objects

convert_objects()

Converts GraphQL edges to File objects.

method Reports.update_variables

update_variables()

Updates the GraphQL query variables for pagination.

class BetaReport

BetaReport is a class associated with reports created in W&B.

WARNING: this API will likely change in a future release

Attributes:

• name (string): The name of the report.
• description (string): Report description.
• user (User): The user that created the report.
• spec (dict): The spec off the report.
• updated_at (string): timestamp of last update.

method BetaReport.__init__

__init__(client, attrs, entity=None, project=None)

property BetaReport.sections

Get the panel sections (groups) from the report.

property BetaReport.updated_at

Timestamp of last update

property BetaReport.url

URL of the report.

Contains the entity, project, display name, and id.

method BetaReport.runs

runs(section, per_page=50, only_selected=True)

Get runs associated with a section of the report.

method BetaReport.to_html

to_html(height=1024, hidden=False)

Generate HTML containing an iframe displaying this report.

11 - runs

module wandb.apis.public

W&B Public API for Runs.

This module provides classes for interacting with W&B runs and their associated data.

Example:

from wandb.apis.public import Api

# Initialize API
api = Api()

# Get runs matching filters
runs = api.runs(
    path="entity/project", filters={"state": "finished", "config.batch_size": 32}
)

# Access run data
for run in runs:
    print(f"Run: {run.name}")
    print(f"Config: {run.config}")
    print(f"Metrics: {run.summary}")

    # Get history with pandas
    history_df = run.history(keys=["loss", "accuracy"], pandas=True)

    # Work with artifacts
    for artifact in run.logged_artifacts():
        print(f"Artifact: {artifact.name}")

Note:

This module is part of the W&B Public API and provides read/write access to run data. For logging new runs, use the wandb.init() function from the main wandb package.

class Runs

An iterable collection of runs associated with a project and optional filter.

This is generally used indirectly using the Api.runs namespace.

Args:

• client: (wandb.apis.public.RetryingClient) The API client to use for requests.
• entity: (str) The entity (username or team) that owns the project.
• project: (str) The name of the project to fetch runs from.
• filters: (Optional[Dict[str, Any]]) A dictionary of filters to apply to the runs query.
• order: (Optional[str]) The order of the runs, can be “asc” or “desc” Defaults to “desc”.
• per_page: (int) The number of runs to fetch per request (default is 50).
• include_sweeps: (bool) Whether to include sweep information in the runs. Defaults to True.

Examples:

from wandb.apis.public.runs import Runs
from wandb.apis.public import Api

# Initialize the API client
api = Api()

# Get all runs from a project that satisfy the filters
filters = {"state": "finished", "config.optimizer": "adam"}

runs = Runs(
   client=api.client,
   entity="entity",
   project="project_name",
   filters=filters,
)

# Iterate over runs and print details
for run in runs:
   print(f"Run name: {run.name}")
   print(f"Run ID: {run.id}")
   print(f"Run URL: {run.url}")
   print(f"Run state: {run.state}")
   print(f"Run config: {run.config}")
   print(f"Run summary: {run.summary}")
   print(f"Run history (samples=5): {run.history(samples=5)}")
   print("----------")

# Get histories for all runs with specific metrics
histories_df = runs.histories(
   samples=100,  # Number of samples per run
   keys=["loss", "accuracy"],  # Metrics to fetch
   x_axis="_step",  # X-axis metric
   format="pandas",  # Return as pandas DataFrame
)

method Runs.__init__

__init__(
    client: 'RetryingClient',
    entity: str,
    project: str,
    filters: Optional[Dict[str, Any]] = None,
    order: Optional[str] = None,
    per_page: int = 50,
    include_sweeps: bool = True
)

property Runs.cursor

Returns the cursor position for pagination of runs results.

property Runs.length

Returns the total number of runs.

property Runs.more

Returns whether there are more runs to fetch.

method Runs.convert_objects

convert_objects()

Converts GraphQL edges to Runs objects.

method Runs.histories

histories(
    samples: int = 500,
    keys: Optional[List[str]] = None,
    x_axis: str = '_step',
    format: Literal['default', 'pandas', 'polars'] = 'default',
    stream: Literal['default', 'system'] = 'default'
)

Return sampled history metrics for all runs that fit the filters conditions.

Args:

• samples: The number of samples to return per run
• keys: Only return metrics for specific keys
• x_axis: Use this metric as the xAxis defaults to _step
• format: Format to return data in, options are “default”, “pandas”, “polars”
• stream: “default” for metrics, “system” for machine metrics

Returns:

• pandas.DataFrame: If format="pandas", returns a pandas.DataFrame of history metrics.
• polars.DataFrame: If format="polars", returns a polars.DataFrame of history metrics.
• list of dicts: If format="default", returns a list of dicts containing history metrics with a run_id key.

class Run

A single run associated with an entity and project.

Args:

• client: The W&B API client.
• entity: The entity associated with the run.
• project: The project associated with the run.
• run_id: The unique identifier for the run.
• attrs: The attributes of the run.
• include_sweeps: Whether to include sweeps in the run.

Attributes:

• tags ([str]): a list of tags associated with the run
• url (str): the url of this run
• id (str): unique identifier for the run (defaults to eight characters)
• name (str): the name of the run
• state (str): one of: running, finished, crashed, killed, preempting, preempted
• config (dict): a dict of hyperparameters associated with the run
• created_at (str): ISO timestamp when the run was started
• system_metrics (dict): the latest system metrics recorded for the run
• summary (dict): A mutable dict-like property that holds the current summary. Calling update will persist any changes.
• project (str): the project associated with the run
• entity (str): the name of the entity associated with the run
• project_internal_id (int): the internal id of the project
• user (str): the name of the user who created the run
• path (str): Unique identifier [entity]/[project]/[run_id]
• notes (str): Notes about the run
• read_only (boolean): Whether the run is editable
• history_keys (str): Keys of the history metrics that have been logged
• with wandb.log({key: value})
• metadata (str): Metadata about the run from wandb-metadata.json

method Run.__init__

__init__(
    client: 'RetryingClient',
    entity: str,
    project: str,
    run_id: str,
    attrs: Optional[Mapping] = None,
    include_sweeps: bool = True
)

Initialize a Run object.

Run is always initialized by calling api.runs() where api is an instance of wandb.Api.

method Run.delete

delete(delete_artifacts=False)

Delete the given run from the wandb backend.

Args:

• delete_artifacts (bool, optional): Whether to delete the artifacts associated with the run.

method Run.file

file(name)

Return the path of a file with a given name in the artifact.

Args:

• name (str): name of requested file.

Returns: A File matching the name argument.

method Run.files

files(names=None, per_page=50)

Return a file path for each file named.

Args:

• names (list): names of the requested files, if empty returns all files
• per_page (int): number of results per page.

Returns: A Files object, which is an iterator over File objects.

method Run.history

history(samples=500, keys=None, x_axis='_step', pandas=True, stream='default')

Return sampled history metrics for a run.

This is simpler and faster if you are ok with the history records being sampled.

Args:

• samples : (int, optional) The number of samples to return
• pandas : (bool, optional) Return a pandas dataframe
• keys : (list, optional) Only return metrics for specific keys
• x_axis : (str, optional) Use this metric as the xAxis defaults to _step
• stream : (str, optional) “default” for metrics, “system” for machine metrics

Returns:

• pandas.DataFrame: If pandas=True returns a pandas.DataFrame of history metrics.
• list of dicts: If pandas=False returns a list of dicts of history metrics.

method Run.load

load(force=False)

Fetch and update run data from GraphQL database.

Ensures run data is up to date.

Args:

• force (bool): Whether to force a refresh of the run data.

method Run.log_artifact

log_artifact(
    artifact: 'wandb.Artifact',
    aliases: Optional[Collection[str]] = None,
    tags: Optional[Collection[str]] = None
)

Declare an artifact as output of a run.

Args:

• artifact (Artifact): An artifact returned from wandb.Api().artifact(name).
• aliases (list, optional): Aliases to apply to this artifact.
• tags: (list, optional) Tags to apply to this artifact, if any.

Returns: A Artifact object.

method Run.logged_artifacts

logged_artifacts(per_page: int = 100) → RunArtifacts

Fetches all artifacts logged by this run.

Retrieves all output artifacts that were logged during the run. Returns a paginated result that can be iterated over or collected into a single list.

Args:

• per_page: Number of artifacts to fetch per API request.

Returns: An iterable collection of all Artifact objects logged as outputs during this run.

Example:

import wandb
import tempfile

with tempfile.NamedTemporaryFile(mode="w", delete=False, suffix=".txt") as tmp:
   tmp.write("This is a test artifact")
   tmp_path = tmp.name
run = wandb.init(project="artifact-example")
artifact = wandb.Artifact("test_artifact", type="dataset")
artifact.add_file(tmp_path)
run.log_artifact(artifact)
run.finish()

api = wandb.Api()

finished_run = api.run(f"{run.entity}/{run.project}/{run.id}")

for logged_artifact in finished_run.logged_artifacts():
   print(logged_artifact.name)

method Run.save

save()

Persist changes to the run object to the W&B backend.

method Run.scan_history

scan_history(keys=None, page_size=1000, min_step=None, max_step=None)

Returns an iterable collection of all history records for a run.

Args:

• keys ([str], optional): only fetch these keys, and only fetch rows that have all of keys defined.
• page_size (int, optional): size of pages to fetch from the api.
• min_step (int, optional): the minimum number of pages to scan at a time.
• max_step (int, optional): the maximum number of pages to scan at a time.

Returns: An iterable collection over history records (dict).

Example: Export all the loss values for an example run

run = api.run("entity/project-name/run-id")
history = run.scan_history(keys=["Loss"])
losses = [row["Loss"] for row in history]

method Run.to_html

to_html(height=420, hidden=False)

Generate HTML containing an iframe displaying this run.

method Run.update

update()

Persist changes to the run object to the wandb backend.

method Run.upload_file

upload_file(path, root='.')

Upload a local file to W&B, associating it with this run.

Args:

• path (str): Path to the file to upload. Can be absolute or relative.
• root (str): The root path to save the file relative to. For example, if you want to have the file saved in the run as “my_dir/file.txt” and you’re currently in “my_dir” you would set root to “../”. Defaults to current directory (".").

Returns: A File object representing the uploaded file.

method Run.use_artifact

use_artifact(artifact, use_as=None)

Declare an artifact as an input to a run.

Args:

• artifact (Artifact): An artifact returned from wandb.Api().artifact(name)
• use_as (string, optional): A string identifying how the artifact is used in the script. Used to easily differentiate artifacts used in a run, when using the beta wandb launch feature’s artifact swapping functionality.

Returns: An Artifact object.

method Run.used_artifacts

used_artifacts(per_page: int = 100) → RunArtifacts

Fetches artifacts explicitly used by this run.

Retrieves only the input artifacts that were explicitly declared as used during the run, typically via run.use_artifact(). Returns a paginated result that can be iterated over or collected into a single list.

Args:

• per_page: Number of artifacts to fetch per API request.

Returns: An iterable collection of Artifact objects explicitly used as inputs in this run.

Example:

import wandb

run = wandb.init(project="artifact-example")
run.use_artifact("test_artifact:latest")
run.finish()

api = wandb.Api()
finished_run = api.run(f"{run.entity}/{run.project}/{run.id}")
for used_artifact in finished_run.used_artifacts():
   print(used_artifact.name)
test_artifact

method Run.wait_until_finished

wait_until_finished()

Check the state of the run until it is finished.

12 - sweeps

module wandb.apis.public

W&B Public API for Sweeps.

This module provides classes for interacting with W&B hyperparameter optimization sweeps.

Example:

from wandb.apis.public import Api

# Initialize API
api = Api()

# Get a specific sweep
sweep = api.sweep("entity/project/sweep_id")

# Access sweep properties
print(f"Sweep: {sweep.name}")
print(f"State: {sweep.state}")
print(f"Best Loss: {sweep.best_loss}")

# Get best performing run
best_run = sweep.best_run()
print(f"Best Run: {best_run.name}")
print(f"Metrics: {best_run.summary}")

Note:

This module is part of the W&B Public API and provides read-only access to sweep data. For creating and controlling sweeps, use the wandb.sweep() and wandb.agent() functions from the main wandb package.

class Sweep

The set of runs associated with the sweep.

Attributes:

• runs (Runs): List of runs
• id (str): Sweep ID
• project (str): The name of the project the sweep belongs to
• config (dict): Dictionary containing the sweep configuration
• state (str): The state of the sweep. Can be “Finished”, “Failed”, “Crashed”, or “Running”.
• expected_run_count (int): The number of expected runs for the sweep

method Sweep.__init__

__init__(client, entity, project, sweep_id, attrs=None)

property Sweep.config

The sweep configuration used for the sweep.

property Sweep.entity

The entity associated with the sweep.

property Sweep.expected_run_count

Return the number of expected runs in the sweep or None for infinite runs.

property Sweep.name

The name of the sweep.

If the sweep has a name, it will be returned. Otherwise, the sweep ID will be returned.

property Sweep.order

Return the order key for the sweep.

property Sweep.path

Returns the path of the project.

The path is a list containing the entity, project name, and sweep ID.

property Sweep.url

The URL of the sweep.

The sweep URL is generated from the entity, project, the term “sweeps”, and the sweep ID.run_id. For SaaS users, it takes the form of https://wandb.ai/entity/project/sweeps/sweeps_ID.

property Sweep.username

Deprecated. Use Sweep.entity instead.

method Sweep.best_run

best_run(order=None)

Return the best run sorted by the metric defined in config or the order passed in.

classmethod Sweep.get

get(
    client,
    entity=None,
    project=None,
    sid=None,
    order=None,
    query=None,
    **kwargs
)

Execute a query against the cloud backend.

method Sweep.load

load(force: bool = False)

Fetch and update sweep data logged to the run from GraphQL database.

method Sweep.to_html

to_html(height=420, hidden=False)

Generate HTML containing an iframe displaying this sweep.

13 - teams

module wandb.apis.public

W&B Public API for managing teams and team members.

This module provides classes for managing W&B teams and their members.

Note:

This module is part of the W&B Public API and provides methods to manage teams and their members. Team management operations require appropriate permissions.

class Member

A member of a team.

Args:

• client (wandb.apis.internal.Api): The client instance to use
• team (str): The name of the team this member belongs to
• attrs (dict): The member attributes

method Member.__init__

__init__(client, team, attrs)

method Member.delete

delete()

Remove a member from a team.

Returns: Boolean indicating success

class Team

A class that represents a W&B team.

This class provides methods to manage W&B teams, including creating teams, inviting members, and managing service accounts. It inherits from Attrs to handle team attributes.

Args:

• client (wandb.apis.public.Api): The api instance to use
• name (str): The name of the team
• attrs (dict): Optional dictionary of team attributes

Note:

Team management requires appropriate permissions.

method Team.__init__

__init__(client, name, attrs=None)

classmethod Team.create

create(api, team, admin_username=None)

Create a new team.

Args:

• api: (Api) The api instance to use
• team: (str) The name of the team
• admin_username: (str) optional username of the admin user of the team, defaults to the current user.

Returns: A Team object

method Team.create_service_account

create_service_account(description)

Create a service account for the team.

Args:

• description: (str) A description for this service account

Returns: The service account Member object, or None on failure

method Team.invite

invite(username_or_email, admin=False)

Invite a user to a team.

Args:

• username_or_email: (str) The username or email address of the user you want to invite.
• admin: (bool) Whether to make this user a team admin. Defaults to False.

Returns: True on success, False if user was already invited or didn’t exist.

method Team.load

load(force=False)

Return members that belong to a team.

14 - users

module wandb.apis.public

W&B Public API for managing users and API keys.

This module provides classes for managing W&B users and their API keys.

Note:

This module is part of the W&B Public API and provides methods to manage users and their authentication. Some operations require admin privileges.

class User

A class representing a W&B user with authentication and management capabilities.

This class provides methods to manage W&B users, including creating users, managing API keys, and accessing team memberships. It inherits from Attrs to handle user attributes.

Args:

• client: (wandb.apis.internal.Api) The client instance to use
• attrs: (dict) The user attributes

Note:

Some operations require admin privileges

method User.__init__

__init__(client, attrs)

property User.api_keys

List of API key names associated with the user.

Returns:

• list[str]: Names of API keys associated with the user. Empty list if user has no API keys or if API key data hasn’t been loaded.

property User.teams

List of team names that the user is a member of.

Returns:

• list (list): Names of teams the user belongs to. Empty list if user has no team memberships or if teams data hasn’t been loaded.

property User.user_api

An instance of the api using credentials from the user.

classmethod User.create

create(api, email, admin=False)

Create a new user.

Args:

• api (Api): The api instance to use
• email (str): The name of the team
• admin (bool): Whether this user should be a global instance admin

Returns: A User object

method User.delete_api_key

delete_api_key(api_key)

Delete a user’s api key.

Args:

• api_key (str): The name of the API key to delete. This should be one of the names returned by the api_keys property.

Returns: Boolean indicating success

Raises: ValueError if the api_key couldn’t be found

method User.generate_api_key

generate_api_key(description=None)

Generate a new api key.

Args:

• description (str, optional): A description for the new API key. This can be used to identify the purpose of the API key.

Returns: The new api key, or None on failure