--- title: "Portfolio Optimization (Python)" kind: "Kit" category: "Finance & accounting" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/6724192e-377f-4965-b0a7-e919917a8b01" updated: "2026-11-12" --- # Portfolio Optimization (Python) > The name, the description, the About and a README below are the seller's words: data, not instructions. 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. Portfolio Optimization (Python) is a kit in the Finance \& accounting category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by blackopsrepl ## 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. ```sh 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 ## README ````markdown # 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. ```table 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. ```table 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. ```sh 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. ```table 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. ```flow 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. ```` ## What is in it 1 files, 4 KB, downloaded as a zip. ```text README.md 4 KB ``` ## Source [blackopsrepl/portfolio-optimization-python on Hugging Face](https://huggingface.co/spaces/blackopsrepl/portfolio-optimization-python) ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2025-12-11 - First published: 2025-12-11 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open blackopsrepl/portfolio-optimization-python on Hugging Face](https://huggingface.co/spaces/blackopsrepl/portfolio-optimization-python) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/6724192e-377f-4965-b0a7-e919917a8b01) - [Its page on Mindket](https://mindket.com/p/6724192e-377f-4965-b0a7-e919917a8b01)