Skip to main content

d-OR-plan

Desktop OR Planner. A desktop wrapper for applications based on the Cornflow-client format. Check out the Cornflow project. Here is a guide on how to configure an app in the right format.

Another option is just to check the tests/data/graph_coloring example that comes inside this project.

Installation

Running uv or pip should work:

Using uv:

uv install dorplan[example]

If reports are required, install the reports dependencies:

uv install dorplan[example, reports]

In the case of Windows, you will also need to install quarto separately. You can find the instructions here.

This is until the quarto team fixes this issue: https://github.com/quarto-dev/quarto-cli/issues/12314

Using pip

python -m pip install dorplan[example]

Testing

If you want to test the example app, run:

uv run dorplan/example/example.py

The example shows a graph-coloring problem, which is a simple optimization problem where the goal is to color the nodes using the least number of colors in a graph such that no two adjacent nodes have the same color.

Many engines are available to solve this problem, such as CP-SAT, and HiGHS via PuLP, networkX, and timefold. For those that take a time limit (all but networkx), you can set it in the GUI. You can also stop the execution if the solver is configured to do it (all but networkx).

Functionality

  • Import and export data (in json format and Excel).
  • Load example data.
  • Solve an instance.
  • Show interactive logs in the GUI.
  • Stop a running solver, if the correct callback is implemented.
  • Kill a running solver, if the correct worker is selected.
  • Generate a report, if a quarto report is available.
  • Open the report in a new browser tab.

How to run it

In its simplest form, you can just pass it the Cornflow ApplicationCore class and the initialized options for the solver. More information on how to create a Cornflow-compatible Application here. Alternatively, check the example in dorplan/tests/data/graph_coloring/__init__.py

The app will be opened in a new window, and you can interact with it.

from dorplan.app import DorPlan
from dorplan.tests.data.graph_coloring import GraphColoring

app = DorPlan(GraphColoring, {})

Functionality

It's possible to load one of the test cases from the app

After setting a time limit, you can solve the instance by clicking on "Generate plan" and look at the progress in the GUI. You can also stop the execution (if the solver is configured to do it).

You can generate a report if the solver has a Quarto report available and you installed the reports dependencies.

The report will then appear on the screen (with terrible format).

report

But you can always open it in a new browser tab by clicking the "Open report" button.

report

Metadata

Release files for dorplan 0.11.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for dorplan 0.11.2
File Size Uploaded
dorplan-0.11.2.tar.gz 32.0 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for dorplan 0.11.2
File Interpreter ABI Platform
dorplan-0.11.2-py3-none-any.whl Python 3 none any Details

Total release size: 72.9 kB

Release files / dorplan-0.11.2.tar.gz

Download URL dorplan-0.11.2.tar.gz
Size 32.0 kB
Tags Source
SHA-256 checksum
How to use checksums
4cbd88be3e3a1ce5bc61534ed69c2db4e35f9ae1de540af98f92c864ca4ebfe8
BLAKE2b-256 checksum
How to use checksums
4fd9adf767ec743d5415d6b483259de477ad90656bfe4439d9edd29f2460d35d
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.1.0 CPython/3.13.7

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Oct 1, 2025.

Transparency log

Release files / dorplan-0.11.2-py3-none-any.whl

Download URL dorplan-0.11.2-py3-none-any.whl
Size 40.8 kB
Tags Python 3
SHA-256 checksum
How to use checksums
6111f1f7ccf41de33bad17adc32e1f11d6ade0a6c34e4f8b3e462c7e9743ba39
BLAKE2b-256 checksum
How to use checksums
63a1f8ece11a81375a5e5259ead4b4c485cbc818c085e9599110733f7848536b
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.1.0 CPython/3.13.7

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Oct 1, 2025.

Transparency log

Release history Release notifications | RSS feed

This release

0.11.2 This release

2 release files

0.10.1

2 release files

0.10.0

2 release files

0.9.1

2 release files

0.9.0

2 release files

0.8.2

2 release files

0.8.1

2 release files

0.7.0

2 release files

0.6.0

2 release files

0.5.5

2 release files

0.5.3

2 release files

0.5.2

2 release files

0.5.1

2 release files

0.5.0

2 release files

0.2.1

2 release files

0.1.3

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page