Runs

class Runs

(service_api: 'ServiceApi',
entity: 'str',
project: 'str',
filters: 'dict[str, Any] | None' = None,
order: 'str' = '+created_at',
per_page: 'int' = 50,
include_sweeps: 'bool' = False,
lazy: 'bool' = True,
api_key: 'str | None' = None)

Description

A lazy iterator of Run objects associated with a project and optional filter.

Runs are retrieved in pages from the W&B server as needed.

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

Args

• service_api: The service API to use for requests.
• entity: The entity (username or team) that owns the project.
• project: The name of the project to fetch runs from.
• filters: Filters to apply to the runs query.
• order: Order can be created_at, heartbeat_at, config.*.value, or summary_metrics.*. If you prepend order with a + order is ascending (default). If you prepend order with a - order is descending. The default order is run.created_at from oldest to newest.
• per_page: The number of runs to fetch per request (default is 50).
• include_sweeps: Whether to include sweep information in the runs. Defaults to True.
• lazy:
• api_key:

Methods

method histories

self,
samples: 'int' = 500,
keys: 'list[str] | None' = 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.

Arguments

• 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

method next

self

Return the next item from the iterator. When exhausted, raise StopIteration

method update_variables

self

Update the query variables for the next page fetch.

method upgrade_to_full

self

Upgrade this Runs collection from lazy to full mode.

This switches to fetching full run data and upgrades any already-loaded Run objects to have full data. Uses parallel loading for better performance when upgrading multiple runs.