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updated pre-commit hooks #235

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updated pre-commit hooks

updated pre-commit hooks #235

Workflow file for this run

.github/workflows/main.yml at a51bbbb
# Train model, evaluate and test champion model, build containerized model, and deploy model
name: CI/CD
on:
push:
branches: ["main"]
# pull_request:
# branches: ["main"]
# Run workflow manually from the Actions tab
workflow_dispatch:
jobs:
train:
runs-on: ubuntu-latest
steps:
# Checks-out repository under $GITHUB_WORKSPACE, so the job can access it
# Use cache action to cache the virtual environment (https://stackoverflow.com/a/62639424)
- uses: actions/checkout@v3
- name: Set up Python 3.10.*
uses: actions/setup-python@v1
with:
python-version: 3.10.*
- name: Get pip cache dir
id: pip-cache
run: echo "PIP_CACHE_DIR=$(pip cache dir)" >> $GITHUB_ENV
# Use cache action to cache the virtual environment
- name: Cache pip dependencies
uses: actions/cache@v2
with:
path: ${{ env.PIP_CACHE_DIR }}
key: ${{ runner.os }}-pip-${{ hashFiles('**/requirements.txt') }}
restore-keys: |
${{ runner.os }}-pip-
- name: Install dependencies
run: |
make install
- name: Add project path to sys.path
run: |
echo "PYTHONPATH=${{github.workspace}}" >> $GITHUB_ENV
- name: Sort imports with isort
run: |
make isort
- name: Format with black
run: |
make format
- name: Test with pytest
run: |
make test
- name: Upload coverage reports to Codecov
uses: codecov/[email protected]
with:
token: ${{ secrets.CODECOV_TOKEN }}
slug: Adeemy/end-to-end-ml
- name: Lint with pylint
run: |
make lint
- name: Prepare data
run: |
make prep_data
- name: Setup Feast
run: |
make setup_feast
- name: Split data
run: |
make split_data
# # The train step is resource intensive and should be on a local machine
# # or on a remote compute cluster. When training is finished, this workflow
# # can be resumed to evaluate the models and test the champion model. This
# # step is not implemented in this project. Thus, the training is run on a
# # local machine at this juncture and train step is included in the CI/CD
# # pipeline for demonstration purposes.
# - name: Trigger train
# env:
# COMET_API_KEY: ${{ secrets.COMET_API_KEY }}
# TRAINING_SSH_KEY: ${{ secrets.TRAINING_SSH_KEY }}
# run: |
# ssh -i ${{ secrets.TRAINING_SSH_KEY }} training@my-cluster "make train"
# # or use a web service:
# # curl -X POST https://my-cluster/start-training
evaluate:
runs-on: ubuntu-latest
needs: train
steps:
- uses: actions/checkout@v3
- name: Set up Python 3.10.*
uses: actions/setup-python@v1
with:
python-version: 3.10.*
- name: Get pip cache dir
id: pip-cache
run: echo "PIP_CACHE_DIR=$(pip cache dir)" >> $GITHUB_ENV
# Use cache action to cache the virtual environment
- name: Cache pip dependencies
uses: actions/cache@v2
with:
path: ${{ env.PIP_CACHE_DIR }}
key: ${{ runner.os }}-pip-${{ hashFiles('**/requirements.txt') }}
restore-keys: |
${{ runner.os }}-pip-
- name: Install dependencies
run: |
make install
- name: Add project path to sys.path
run: |
echo "PYTHONPATH=${{github.workspace}}" >> $GITHUB_ENV
# The latest version of the champion model is pulled from model registry
# and evaluated in this step. If the model performance meets the deployment
# criteria, the model is then packaged in the build job to deployed in the
# production environment.
- name: Evaluate models
env:
COMET_API_KEY: ${{ secrets.COMET_API_KEY }}
run: |
make evaluate
- name: Test champion model
env:
COMET_API_KEY: ${{ secrets.COMET_API_KEY }}
run: |
make test_model
build:
runs-on: ubuntu-latest
needs: evaluate
steps:
- uses: actions/checkout@v3
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v1
# Login using same GitHub Actions credentials
- name: Log in to GitHub container registry
uses: docker/[email protected]
with:
registry: ghcr.io
username: ${{ github.actor }}
password: ${{ github.token }}
# Ensures that repo name is lowercase, which is a requirement for publishing to ghcr.io
- name: Lowercase the repo name and username
run: echo "REPO=${GITHUB_REPOSITORY,,}" >>${GITHUB_ENV}
- name: Build and push container image to registry
uses: docker/build-push-action@v2
with:
push: true
tags: ghcr.io/${{ env.REPO }}:${{ github.sha }}
file: ./src/inference/Dockerfile