Baummethoden

4 Tickets

• Task 1: Daten herunterladen
• Task 2: Modell trainieren und mit train.py im Terminal ausführen
• Task 3: Modell speichern (als pickle File)
• Task 4: Modell im predict.py file laden und im Terminal ausführen

Setup

Linux Users

• create new python environment: python3 -m venv .venv
• activate python environment: source .venv/bin/activate
• install dependencies: pip install -r requirements.txt

Windows Users

• create new python environment: python -m venv .venv
• activate python environment: .\.venv\Scripts\Activate.ps1
• install dependencies: pip install -r requirements.txt

Development

• activate python environment: source .venv/bin/activate
• run python script: python <filename.py> , e.g. python train.py
• install new dependency: pip install sklearn
• save current installed dependencies back to requirements.txt: pip freeze > requirements.txt
• start python api with python wsgi.py

Set Up API Hosting

• Create a heroku account
• Create a new app and save the name
• Go to your Account Settings and save the API Key
• Go to the secrets in the settings of your GitHub repository
• Add the API Key as HEROKU_API_KEY
• Add the app name as HEROKU_APP_NAME
• Add your email address (the one you used for creating the heroku account) as HEROKU_EMAIL
• The github actions scripts assumes that a heroku branch exists. If it doesn't, create the branch
• After the first successful github actions deployment, you should be able to access the api via https://<your-app-name>.herokuapp.com

GitHub Actions within this repository

pull-request

• action that is run on every pull request open and synchronize event

on:
  pull_request:
    types: [opened, synchronize]

• the action will run train.py and upload the model as an artifact inside the action

production-release

• action that is run on every pushin the main branch (that also includes merges from any other branch to main branch)

on:
  push:
    branches:
      - main

• the action will run train.py and upload the model as an artifact inside the action
• the action will create or checkout a branch called heroku and merge main to heroku
• the action will deploy the code to heroku hosting and run the API, see the action documentation for more information

Useful commands

• init new git repository: git init
• add https://github.com/example/repo.git as remote repository: git remote add origin https://github.com/example/repo.git
• check configured remote: git remote -v
• stage file/directory for commit: git add <file or directory>
• commit with message: git commit - m "message"
• show git history of current branch: git log
• create new branch with history from current branch: git branch <branchname>
• check out branch: git checkout <branchname>
• pull changes from remote branch into current branch: git pull
• push and set remote branchname, always set the same name as local branch name: git push --set-upstream origin <branchname>
• push changes to existing remote branch: git push
• create new python environment: python3 -m venv .venv
• activate python environment: source .venv/bin/activate
• show installed python dependencies: pip freeze
• show installed python dependencies & save to requirements.txt file: pip freeze > requirements.txt
• install dependencies from file: pip install -r requirements.txt
• install single pandas dependency pip install pandas
• checkout git branch (if exists) or create a new one (if it does not exist): git checkout foo 2>/dev/null || git checkout -b foo, see https://stackoverflow.com/questions/26961371/switch-on-another-branch-create-if-not-exists-without-checking-if-already-exi