Portfolio Optimization (Python)

Portfolio Optimization (Python)

Shows a portfolio optimization problem from SolverForge as a Docker app that you open in a browser or build on your own machine. For people exploring solver demos in finance.

Made by blackopsrepl on Hugging Face. These notes are Mindket's, written from its Space page and README; the app's own files and license are on Hugging Face.

About

What it is: This Space holds a portfolio optimization problem from SolverForge, written in Python and packaged as a Docker app. You can open it in a browser with nothing to install. The repository also carries source code, a static folder, tests and a logging setup, so you can build your own copy.

Who it suits: It suits people who want to see an optimization problem for investment portfolios running, and developers who want a Docker and Python project to read.

Industry | Who uses it | How they use it | Example
Finance | Analysts and students | Open the hosted app to see a portfolio optimization problem in action | Look at how a solver demo is presented
Software | Python developers | Read the source, tests and Dockerfile of a solver project | Copy the project layout for their own demo
Education | Teachers of optimization | Use the running demo as a classroom example | Show the demo on a shared screen

You can skip it if you need a tool to manage a real portfolio, since the source only calls it a problem demo.

Where to use it:

• A web browser: open the Space page on Hugging Face. It runs on cpu-basic hardware there.
• Windows, macOS or Linux with Docker: build the image and run it yourself.

Use case | Who | What they get back
Try the demo | Anyone | The running portfolio optimization app in the browser
Read the project | Developers | Source, tests, a Dockerfile and a logging config
Run a private copy | Developers | A container that listens on port 8080

How to set it up: The hosted page needs nothing from you. A local copy needs these things first.

• Docker on Windows, macOS or Linux.
• Python and pip, to download the files with the hf command.

1. Install the huggingface_hub package with pip.
2. Download the Space's files into a folder with the hf command.
3. Move into that folder.
4. Build the Docker image from the Dockerfile.
5. Run the image and map port 8080.

pip install -U huggingface_hub
hf download blackopsrepl/portfolio-optimization-python --repo-type space --local-dir portfolio-optimization-python
cd portfolio-optimization-python
docker build -t portfolio-optimization-python .
docker run -it -p 8080:8080 portfolio-optimization-python

How to use it: Online, open the Space page. On your own computer, run the last two commands above and open port 8080 in your browser. The repository says little about the app's controls, so look at the page itself.

Tool | What it does
docker build | Builds the image from the Dockerfile in the folder
docker run | Starts the container and maps port 8080
src | Holds the source code
tests | Holds the project's tests

Example: You download the Space, build the image and run it with port 8080 mapped. You then open that port in a browser, and the portfolio optimization demo loads from your own machine.

For newcomers and experts: If you are new, open the hosted page first. It needs nothing installed, and you can look at how the problem is shown. Try a local build only after that.

If you know the field, this is a Docker Space on port 8080 with Python code in src, a pyproject.toml, a static folder, a logging.conf and a tests folder. It runs on cpu-basic hardware. The repository does not describe the solver model or the constraints.

Open the Space or build the image
The Docker container starts on port 8080
You open the app in a browser

Good to know: The README is a single line, so details about the problem itself are not documented there.

• License: apache-2
• Cost to run: none named
• Data it reaches: none named
• Needs: Docker for a local copy

On Hugging Face, 13 November 2026

• Likes: 2
• Built with: docker
• License: apache-2.0

Links

• Space: https://huggingface.co/spaces/blackopsrepl/portfolio-optimization-python
• Files: https://huggingface.co/spaces/blackopsrepl/portfolio-optimization-python/tree/main

Try it

Open the Space in your browser, or copy it to your own Hugging Face account from its page. Nothing in this kit runs by itself.