fetch_experiments_table()
Fetches a table of experiment metadata, with runs as rows and attributes as columns.
To narrow the results, define filters for experiments 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
Path of the Neptune project, as WorkspaceName/ProjectName
.
If not provided, the NEPTUNE_PROJECT
environment variable is used.
Filter specifying which experiments to include.
- If a string is provided, it's treated as a regex pattern that the experiment names must match.
- If a list of strings is provided, it's treated as exact experiment names to match.
- To provide a more complex condition on an arbitrary attribute value, pass a
Filter
object.
If no filter is specified, all experiments are returned.
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.
Name of the attribute to sort the table by.
Alternatively, an Attribute
object that specifies the attribute type.
Sorting direction of the column specified by the sort_by
parameter.
Maximum number of experiments to return. By default all experiments are returned.
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.
Example
Fetch attributes matching loss
or configs
from two specific experiments:
import neptune_query as nq
nq.fetch_experiments_table(
experiments=["seagull-week1", "seagull-week2"],
attributes=r"loss | configs",
)