MLOps ODS

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 .

Metadata

Release files for mlops-ods 0.1.202406130811

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for mlops-ods 0.1.202406130811
File	Size	Uploaded	Provenance	Actions
mlops_ods-0.1.202406130811.tar.gz	1.5 MB	Jun 13, 2024	Without provenance	Details for mlops_ods-0.1.202406130811.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for mlops-ods 0.1.202406130811
File	Interpreter	ABI	Platform	Actions Reset
mlops_ods-0.1.202406130811-py3-none-any.whl 1.6 MB Jun 13, 2024 Without provenance	Python 3	none	any	Details for mlops_ods-0.1.202406130811-py3-none-any.whl

Total release size: 3.1 MB

Release files / mlops_ods-0.1.202406130811.tar.gz

Download URL	mlops_ods-0.1.202406130811.tar.gz
Size	1.5 MB
Tags	Source
SHA-256 checksum How to use checksums	`2f6a8b799daf7e417abf6ae33d927bcd972d6cbbfd91b174309a4803579d1f46`
BLAKE2b-256 checksum How to use checksums	`16631e0ddc757b8e07606d8e629da8c307880cdf6430a7c7ed762a782c7c517e`
Upload date	Jun 13, 2024
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/5.1.0 CPython/3.9.19`

Release files / mlops_ods-0.1.202406130811-py3-none-any.whl

Download URL	mlops_ods-0.1.202406130811-py3-none-any.whl
Size	1.6 MB
Tags	Python 3
SHA-256 checksum How to use checksums	`0433e2eb2e9eea0421587cbd81367b191f9b04a79c7db71f07ca36bd2fff7829`
BLAKE2b-256 checksum How to use checksums	`f4dda6bef5f47d44f967ea782a918f70d15ff80bb1c55ec748764da926973e38`
Upload date	Jun 13, 2024
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/5.1.0 CPython/3.9.19`

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