semvec/pypi-packages huggingface dataset:
librecubo_clouds 0.0.1
This is a template repository for Python projects that use Poetry for their dependency management.
Requires Python: >=3.9,<4.0

# librecubo-clouds

[![Release](https://img.shields.io/github/v/release/Julio/librecubo-clouds)](https://img.shields.io/github/v/release/Julio/librecubo-clouds)
[![Build status](https://img.shields.io/github/actions/workflow/status/Julio/librecubo-clouds/main.yml?branch=main)](https://github.com/Julio/librecubo-clouds/actions/workflows/main.yml?query=branch%3Amain)
[![codecov](https://codecov.io/gh/Julio/librecubo-clouds/branch/main/graph/badge.svg)](https://codecov.io/gh/Julio/librecubo-clouds)
[![Commit activity](https://img.shields.io/github/commit-activity/m/Julio/librecubo-clouds)](https://img.shields.io/github/commit-activity/m/Julio/librecubo-clouds)
[![License](https://img.shields.io/github/license/Julio/librecubo-clouds)](https://img.shields.io/github/license/Julio/librecubo-clouds)

This is a template repository for Python projects that use Poetry for their dependency management.

- **Github repository**: <https://github.com/Julio/librecubo-clouds/>
- **Documentation** <https://Julio.github.io/librecubo-clouds/>

## Getting started with your project

First, create a repository on GitHub with the same name as this project, and then run the following commands:

```bash
git init -b main
git add .
git commit -m "init commit"
git remote add origin git@github.com:Julio/librecubo-clouds.git
git push -u origin main
```

Finally, install the environment and the pre-commit hooks with

```bash
make install
```

You are now ready to start development on your project!
The CI/CD pipeline will be triggered when you open a pull request, merge to main, or when you create a new release.

To finalize the set-up for publishing to PyPi or Artifactory, see [here](https://fpgmaas.github.io/cookiecutter-poetry/features/publishing/#set-up-for-pypi).
For activating the automatic documentation with MkDocs, see [here](https://fpgmaas.github.io/cookiecutter-poetry/features/mkdocs/#enabling-the-documentation-on-github).
To enable the code coverage reports, see [here](https://fpgmaas.github.io/cookiecutter-poetry/features/codecov/).

## Releasing a new version

- Create an API Token on [Pypi](https://pypi.org/).
- Add the API Token to your projects secrets with the name `PYPI_TOKEN` by visiting [this page](https://github.com/Julio/librecubo-clouds/settings/secrets/actions/new).
- Create a [new release](https://github.com/Julio/librecubo-clouds/releases/new) on Github.
- Create a new tag in the form `*.*.*`.

For more details, see [here](https://fpgmaas.github.io/cookiecutter-poetry/features/cicd/#how-to-trigger-a-release).

---

Repository initiated with [fpgmaas/cookiecutter-poetry](https://github.com/fpgmaas/cookiecutter-poetry).
dummy-app 0.0.2
My dummy dash app
Requires Python: >=3.8.18,<4.0.0

# dummy_app

# Planning
  - Create model train + score api -- done
  - Write training/test data to db -- done
      - update model train to read database -- done
          - to do:  need to figure how to pass large datasets through api - jsonify?
  - create dash app that can visualise -- done
      - train/test data scatter plot with linear model predictions
      - return predictions
          - to do: update to make prettier and include time stamps etc.....
  - stand up ci/cd practices - done
      - set up git hooks - done
          - linting pre-hooks?
          - pytest unit tests?
      - github actions - done
          - Steps
          - build simple tests
          - run on github actions on push
  - create docker file that can run and query data -- done
      - docker to create and publish dockerfile
  - Package pipeline - done
    - Test building + importing package -- done
    - Publish package -- done
  - Convert env to poetry - done
  - Host App + serve dataset on cloud platform
      - Get app to deploy to hosted service
        - how to connect api to app -- done
            - Update Docker App 
                - use Gunicorn
                - Run API + App in same env -- done
                    -  https://docs.docker.com/config/containers/multi-service_container/
      - Get deployment to use package
      - Connect deployments to github actions
      
  
# Useful code
```
# Poetry
poetry update
poetry install
poetry build
poetry config pypi-token.pypi  <token>
poetry publish -- build

# Run app
python  dummy_app/model_api_v2.py & 
sleep 5 
python dummy_app/app.py

# Docker commands
docker ps
docker run -d -it flask-api-image bash
docker exec -it ubuntu bash
docker exec -it flask-api-image bash
docker exec -it <container id or name> bash

# Other 
docker-compose down  # Stop container on current dir if there is a docker-compose.yml
docker rm -fv $(docker ps -aq)  # Remove all containers
sudo lsof -i -P -n | grep 8000 # List who's using the port
sudo lsof -i -P -n | grep python 

# Kill jobs
sudo lsof -i -P -n | grep python 
sudo lsof -i -P -n | grep python | awk '{print $2}'
sudo lsof -i -P -n | grep python | awk '{print $2}' | xargs sudo kill -9 
```