fetch_metrics()

Python package: neptune-fetcher

Returns raw values for the requested metrics. The returned values don't include any aggregation, approximation, or interpolation.

Related

• Fetch metadata via API

Fetch experiment metrics

You can filter the results by:

• Experiments: Specify which experiments to search.
• Attributes: Only list attributes that match certain criteria.

Parameters

experiments

str | list[str] | Filter

required

A filter specifying which experiments to include:

• a regex that the experiment name must match, or
• a list of specific experiment names, or
• a Filter object.

attributes

str | list[str] | AttributeFilter

required

A filter specifying which attributes to include in the table:

• a regex that the attribute name must match, or
• a list of specific attribute names, or
• an AttributeFilter object.

If AttributeFilter.aggregations is set, an exception will be raised as they're not supported in this function.

include_time

"absolute"

optional

default: None

Whether to include absolute timestamp. If set, each metric column has an additional sub-column with requested timestamp values.

step_range

Tuple[float, float]

required

default: None

A tuple specifying the range of steps to include. Can represent an open interval.

lineage_to_the_root

bool

required

default: True

If True, includes all points from the complete experiment history. If False, only includes points from the selected experiment.

tail_limit

int

optional

default: None

From the tail end of each series, how many points to include at most.

type_suffix_in_column_names

bool

required

default: False

If True, columns of the returned DataFrame will be 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.

include_point_previews

bool

optional

default: False

If set to True, metric previews are included in the fetched data frame.

context

Context

optional

default: None

Which project and API token to use for the fetching operation. Useful for switching projects.

Example

Fetch loss metrics from experiments matching a regex, including point previews and only values logged from step 1000 onward:

import neptune_fetcher.alpha as npt


npt.fetch_metrics(
    experiments=r"seagull.*_estimated$",
    attributes=r"^loss/.*",
    step_range=(1000.0, None),
    include_point_previews=True,
)

Output

                            path     loss/train
                                     is_preview     preview_completion	 value
               experiment   step			
seagull-45xc099_estimated   1000.0        False	                   1.0	 0.193153
                            1001.0        False	                   1.0	 0.166237
                            1002.0        False	                   1.0	 0.12602
...

Fetch run metrics

You can filter the results by:

• Runs: Specify which runs to search.
• Attributes: Only list attributes that match certain criteria.

Parameters

runs

str | list[str] | Filter

required

A filter specifying which runs to include:

• a regex that the run ID must match, or
• a list of specific run IDs, or
• a Filter object.

attributes

str | list[str] | AttributeFilter

required

A filter specifying which attributes to include in the table:

• a regex that the attribute name must match, or
• a list of specific attribute names, or
• an AttributeFilter object.

If AttributeFilter.aggregations is set, an exception will be raised as they're not supported in this function.

include_time

"absolute"

optional

default: None

Whether to include absolute timestamp. If set, each metric column has an additional sub-column with requested timestamp values.

step_range

Tuple[float, float]

required

default: None

A tuple specifying the range of steps to include. Can represent an open interval.

lineage_to_the_root

bool

required

default: True

If True, includes all points from the complete run history. If False, only includes points from the selected run.

tail_limit

int

optional

default: None

From the tail end of each series, how many points to include at most.

type_suffix_in_column_names

bool

required

default: False

If True, columns of the returned DataFrame will be 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.

include_point_previews

bool

optional

default: False

If set to True, metric previews are included in the fetched data frame.

context

Context

optional

default: None

Which project and API token to use for the fetching operation. Useful for switching projects.

Example

Fetch accuracy metrics from runs matching a regex, including the last 3 values from each series:

from neptune_fetcher.alpha import runs


runs.fetch_metrics(
    runs=r"marigold",
    attributes=r"accuracy",
    tail_limit=3,
)

Output

                                    accuracy
                              run   step
arrogant-millipede+marigold-finch   49.0	0.830062
                                    50.0	0.828428
                                    51.0	0.825925
 marigold-finch+realistic-dolphin   31.0	0.970358
                                    32.0	0.986717
                                    33.0	0.971492
 marigold-finch+thundering-mantis   29.0	0.925642
                                    30.0	0.963742
                                    31.0	0.970358