Output

Reference

Find the reference for the output module here.

Write the output data after a run is completed.

JSON outputs

Work with JSONoutput.

import nextmv

output = nextmv.Output(
    solution={"foo": "bar"},
    statistics=nextmv.Statistics(
        result=nextmv.ResultStatistics(
            duration=1.0,
            value=2.0,
            custom={"custom": "result_value"},
        ),
        run=nextmv.RunStatistics(
            duration=3.0,
            iterations=4,
            custom={"custom": "run_value"},
        ),
    ),
)

# Write to stdout.
nextmv.write(output)

# Write to a file.
nextmv.write(output, path="output.json")

The solution property of the output is a dictionary that represents the output data. The statistics property can be a nextmv.Statistics object, or a dictionary.

By default, nextmv.Output serializes JSON using pretty printing. If you want to change the serialization behavior, you can pass the json_configurations parameter. The provided values are passed to the underlying json.dumps method. For example, to get compressed output, you can set:

output = nextmv.Output(
    # ...
    json_configurations={
        "indent": None,  # No indentation for compact output
        "separators": (",", ":")  # Use compact separators
    },
    # ...
)

CSV output

Work with one, or multiple, CSV files. In the solution property of the output, the keys are the filenames and the values are the dataframes, represented as a list of dictionaries.

import nextmv

output = nextmv.Output(
    output_format=nextmv.OutputFormat.CSV_ARCHIVE,
    solution={
        "output": [
            {"name": "Alice", "age": 30},
            {"name": "Bob", "age": 40},
        ],
    },
    statistics=nextmv.Statistics(
        result=nextmv.ResultStatistics(
            duration=1.0,
            value=2.0,
            custom={"custom": "result_value"},
        ),
        run=nextmv.RunStatistics(
            duration=3.0,
            iterations=4,
            custom={"custom": "run_value"},
        ),
    ),
)

# Write multiple CSV fiules to a dir named "output".
nextmv.write(output)

# Write multiple CSV files to a custom dir.
nextmv.write(output, "custom_dir")

Similarly to the JSON output, the statistics property can be a nextmv.Statistics object, or a dictionary.

By default, nextmv.Output serializes CSV using , as the separator. If you want to change the serialization behavior, you can pass the csv_configurations parameter. The provided values are passed to the underlying csv.DictWriter method. For example, to use ; as the separator, you can set:

output = nextmv.Output(
    # ...
    csv_configurations={
        "delimiter": ";",  # Use semicolon as the separator
    },
    # ...
)

Assets

A run in Nextmv Cloud can include custom assets, such as those used in custom visualization.

You can use the assets property of the output to include these assets.

Example

You can create a simple plot, which consists of a Plotly bar chart with radius and distance for a planet. Consider the following visuals.py file:

import json

import nextmv
import plotly.graph_objects as go


def create_visuals(name: str, radius: float, distance: float) -> list[nextmv.Asset]:
    """Create a Plotly bar chart with radius and distance for a planet."""

    fig = go.Figure()
    fig.add_trace(
        go.Bar(x=[name], y=[radius], name="Radius (km)", marker_color="red", opacity=0.5),
    )
    fig.add_trace(
        go.Bar(x=[name], y=[distance], name="Distance (Millions km)", marker_color="blue", opacity=0.5),
    )
    fig.update_layout(
        title="Radius and Distance by Planet", xaxis_title="Planet", yaxis_title="Values", barmode="group"
    )
    fig = fig.to_json()

    assets = [
        nextmv.Asset(
            name="Plotly example",
            content_type="json",
            visual=nextmv.Visual(
                visual_schema=nextmv.VisualSchema.PLOTLY,
                visual_type="custom-tab",
                label="Charts",
            ),
            content=[json.loads(fig)],
        )
    ]

    return assets

This list of assets can be included in the output.

import nextmv
from visuals import create_visuals

# Read the input from stdin.
input = nextmv.load()
name = input.data["name"]

options = nextmv.Options(
    nextmv.Option("details", bool, True, "Print details to logs. Default true.", False),
)

##### Insert model here

# Print logs that render in the run view in Nextmv Console.
message = f"Hello, {name}"
nextmv.log(message)

if options.details:
    detail = "You are", {input.data["distance"]}, " million km from the sun"
    nextmv.log(detail)

assets = create_visuals(name, input.data["radius"], input.data["distance"])

# Write output and statistics.
output = nextmv.Output(
    options=options,
    solution=None,
    statistics=nextmv.Statistics(
        result=nextmv.ResultStatistics(
            value=1.23,
            custom={"message": message},
        ),
    ),
    assets=assets,
)
nextmv.write(output)

The assets can be a list of nextmv.Asset objects, or a list of dictionaries that comply with the custom assets and custom visualization schemas, whichever the case may be.