Skip to main content

makina-runway

Project description

Software Development Kit

  • support only python

Goal

  • mlflow를 사용하는 사용자들이 import만 변경하여 runway에 logging하는 방식을 제공한다.
  • runway sdk 는 mlflow 의 interface/arguments 를 최대한 맞추는 방향으로 구현해야 한다.
# import mlflow
from runway import mlflow

with mlflow.start_run() as run:
    mlflow.log_param()

mlflow.sklearn.save_model()

Install

  • makina 사내 pypi server에서 install 합니다.
  1. pip install

    # pip install
    pip install --index-url http://pypi.makina.rocks/simple/ --trusted-host pypi.makina.rocks runway
    
    pyproject.toml의 version 수정 후 테스트 시
    pip install --index-url http://pypi.makina.rocks/simple/ --trusted-host pypi.makina.rocks mrx-runway=={{version}}
    
  2. poetry 사용

    1. pyproject.toml에 사내 pypi source 추가

      [[tool.poetry.source]]
      name = "mrx"
      url = "http://pypi.makina.rocks/simple/"
      default = true
      
    2. poetry add & install

      poetry add runway
      poetry install
      

Publish

  • 정식 version은 runway repo의 tag로 관리됨
  • pyproject.toml 파일의 version은 developer의 test를 위한 pseudo-version 임
  • local에서 publish test는 make command 사용
    # version patch, build & publish 한꺼번에 수행
    make publish-dev
    

How to test in local environment

  • sdk 개발시 local 에서 unit test 실행방식은 아래와 같습니다. utest 시에는 다양한 mlframework package 가 설치되니, 별도의 명령어보다는 makefile 의 recipe 를 사용하시기 바랍니다.
make utest
```bash

## How to develop
- sdk 개발을 위한 `python` 환경을 하나  생성합니다.
- edit 모드로 sdk를 설치 합니다.
```bash
pip install -e .
  • /etc/hosts에 minio관련 host를 추가합니다.
  • misc/gw.yaml, misc/vs.yaml을 수정하여 배포합니다.
  • prepare_develop.sh파일에 BACKEND_URL, MLFLOW_URL, MINIO_URL를 환경에 맞게 수정합니다.
  • prepare_develop.sh를 실행합니다.
./prepare_develop.sh
  • 실행
DEPLOY_TARGET=dev python examples/sample_log_model.py

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

mrx_runway-0.0.2409271440-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.9 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

mrx_runway-0.0.2409271440-cp39-cp39-macosx_10_15_x86_64.whl (913.3 kB view details)

Uploaded CPython 3.9 macOS 10.15+ x86-64

File details

Details for the file mrx_runway-0.0.2409271440-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for mrx_runway-0.0.2409271440-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 7d2c8d74a299d9b89aad13c2b7632cbd2a3b25202c3f644557992eef7ec2dc35
MD5 a3389f19fe1248e1c1365561c6ef063e
BLAKE2b-256 b8e23da1ec55c5b3dc8e69ba8a8ae35682994fd4cb4f5024e0b721adb17d065c

See more details on using hashes here.

File details

Details for the file mrx_runway-0.0.2409271440-cp39-cp39-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for mrx_runway-0.0.2409271440-cp39-cp39-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 65fd7d4d8fe6d02d1bd24152c6e1b0409a72a271d01b7ce3c300d5a8a39c7f4b
MD5 be6062f9b2801317607e179da201cee2
BLAKE2b-256 304d5be0d0f102c2969ef3d1bac09e60091ddbb26fb667ca5d4ed3c40e0280f8

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page