---
title: QuantumProgramResult (latest version)
description: API reference for samplomatic.quantum_program.QuantumProgramResult in the latest version of samplomatic
source: https://quantum.cloud.ibm.com/docs/en/api/samplomatic/auto/quantum-program-quantum-program-result
---

# QuantumProgramResult

*class* `samplomatic.quantum_program.QuantumProgramResult(data: Sequence[dict[str, ndarray] | QuantumProgramItemResult], passthrough_data: list[list[DataTree] | dict[str, DataTree] | ndarray[float] | str | float | int | bool | None] | dict[str, list[DataTree] | dict[str, DataTree] | ndarray[float] | str | float | int | bool | None] | ndarray[float] | str | float | int | bool | None = None)`

[GitHub](https://github.com/Qiskit/samplomatic/tree/main/samplomatic/quantum_program/quantum_program_result.py#L198-L270)

Bases: [`object`](https://docs.python.org/3/builtins/functions.html#object)

A container to store results from executing a [`QuantumProgram`](/docs/api/samplomatic/auto/quantum-program-quantum-program "samplomatic.quantum_program.QuantumProgram").

**Parameters**

- **data** – A list of dictionaries with array-valued data.
- **passthrough\_data** – Arbitrary nested data passed through execution without modification.

**Attributes Summary**

|                                                                                                                                |                                                |
| ------------------------------------------------------------------------------------------------------------------------------ | ---------------------------------------------- |
| [`timing`](#samplomatic.quantum_program.QuantumProgramResult.timing "samplomatic.quantum_program.QuantumProgramResult.timing") | Execution timing information of these results. |

**Attributes Documentation**

### timing

Execution timing information of these results.

A single executor job may be broken up into chunks of work that are executed serially. This property stores information about their timing. Most notably, for each chunk of execution, a start and stop timestamp are provided that bound the window in which the data was collected.

To draw the timings for a single result:

```python
job.result().timing.draw()
```

To draw the timings for several results on one plot:

```python
from samplomatic.visualization.draw_chunk_timings import draw_chunk_timings

draw_chunk_timings(
    job1.result().timing,
    job2.result().timing,
    names=["job 1", "job 2"],
    common_start=True,
)
```

**Returns**

A [`ChunkTiming`](/docs/api/samplomatic/auto/quantum-program-chunk-timing "samplomatic.quantum_program.ChunkTiming") collection.