fetch_experiments_table()

Python package: neptune-query

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.

Parameters

project

str

optional

default: None

Path of the Neptune project, as WorkspaceName/ProjectName.

If not provided, the NEPTUNE_PROJECT environment variable is used.

experiments

str | list[str] | Filter

optional

default: None

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.

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"

Name of the attribute to sort the table by.

Alternatively, an Attribute object that specifies the attribute type.

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.

Returns

pandas.DataFrame – A DataFrame similar to the runs table in the web app.

The DataFrame has:

• a single-level index "experiment" with experiment names
• a single-level column index with attribute names

For series attributes, the last logged value is returned.

Raises

• AttributeTypeInferenceError – If the attribute type wasn't specified in a filter passed to the experiments argument, and the attribute has multiple types across the project's experiments.
• ConflictingAttributeTypes – If there are conflicting attribute types under the same path and the type_suffix_in_column_names argument is set to False.

Example

Fetch attributes matching loss or batch_size from four specific experiments:

import neptune_query as nq


nq.fetch_experiments_table(
    experiments=["seabird-1", "seabird-2", "seabird-3", "seabird-4"],
    attributes=r"loss | batch_size",
    type_suffix_in_column_names=True,
)

Sample output

            config/batch_size:float  config/batch_size:int  loss:float_series
experiment
seabird-4                      64.0                    NaN           0.181736
seabird-3                       NaN                   64.0           0.123372
seabird-2                       NaN                   32.0           0.224408
seabird-1                       NaN                   32.0           0.205908