This project for ml model with MLOps instruments
the methodology of repo (GitHub flow - one main branch, and developing in other brunches):
- main branch: 'master'
- other branches: 'fix-', 'feature-', 'model-', 'experiment-'
poetry build --format=wheel
Docker image (build / run):
docker build . -t mlops_ods_image
docker run -it mlops_ods_image /bin/bash
build for linux:
docker build . -t mlops_ods_image --platform linux/amd64
run with port and volumes if necessary:
docker run -p 8888:8888 -v {path-to-local-folder-(pwd)}:/app/volumes -it mlops_ods_image /bin/bash
documentation of jupyter notebooks with quarto:
quarto render
quarto preview src/mlops_ods/notebooks/eda.ipynb
quarto render src/mlops_ods/notebooks/eda.ipynb --to html
snakemake command inside docker:
snakemake --cores 10
snakemake --dag | dot -Tsvg > dag.svg
docker ps
docker cp <CONTAINER ID>:/app/dag.svg .
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