fetch_runs_table()

Fetches a table of run metadata, with runs as rows and attributes as columns.

To narrow the results, define filters for runs to search or attributes to include.

Returns a DataFrame similar to the runs table in the web app. For series attributes, the last logged value is returned.

Parameters

project

str

optional

default: None

Path of the Neptune project, as WorkspaceName/ProjectName.

If not provided, the NEPTUNE_PROJECT environment variable is used.

runs

str | list[str] | Filter

optional

default: None

Filter specifying which runs to include.

• If a string is provided, it's treated as a regex pattern that the run IDs must match.
• If a list of strings is provided, it's treated as exact run IDs to match.
• To provide a more complex condition on an arbitrary attribute value, pass a Filter object.

If no filter is specified, all runs are returned.

attributes

str | list[str] | AttributeFilter

optional

default: None

Filter specifying which attributes to include.

• If a string is provided, it's treated as a regex pattern that the attribute names must match.
• If a list of strings is provided, it's treated as exact attribute names to match.
• To provide a more complex condition, pass an AttributeFilter object.

sort_by

str | Attribute

optional

default: "sys/creation_time"

An attribute name or an Attribute object specifying type and, optionally, aggregation.

sort_direction

"asc" | "desc"

optional

default: "desc"

Sorting direction of the column specified by the sort_by parameter.

limit

int

optional

default: None

Maximum number of experiments to return. By default all experiments are returned.

type_suffix_in_column_names

bool

optional

default: False

If True, columns of the returned DataFrame are suffixed with :<type>. For example, "attribute1:float_series", "attribute1:string".

If set to False, the method throws an exception if there are multiple types under one path.

Examples

Fetch constituent runs of an experiment, with attributes matching loss or configs as columns:

import neptune_query.runs as nq_runs
from neptune_query.filters import Filter


nq_runs.fetch_runs_table(
    runs=Filter.eq("sys/name", "exp-week9"),
    attributes=r"loss | configs",
)