This release is a pre-release and may not be stable for production use.
mls-model-registry (sktmls)
Contents
Description
A Python package for MLS model registry.
This python package includes
- Customized prediction pipelines inheriting MLSModel
- Model uploader to AWS S3 for meta management and online prediction
Installation
Installation is automatically done by training containers in YE. If you want to install manually for local machines,
# develop
pip install --index-url https://test.pypi.org/simple/ --no-deps sktmls
# production
pip install sktmls
How to use
- MLS Docs: https://ab.sktmls.com/docs/model-registry
- sktmls Docs: https://sktaiflow.github.io/mls-sdk/sktmls
Development
Requirements for development
- Python 3.6
- requirements.txt
- requirements-dev.txt
Local model registry
To enable all model related features in local environment, you need to create a directory models in your home directory.
$ cd ~/
$ mkdir models
Python environment
First you need to do the followings
$ python -V # Check if the version is 3.6.
$ python -m venv env # Create a virtualenv.
$ . env/bin/activate # Activate the env.
$ pip install "numpy>=1.19.4,<1.20" # Install numpy to avoid a requirement error.
$ pip install -r requirements.txt # Install required packages.
$ pip install -r requirements-dev.txt # Install required dev packages.
Documents generation
Before a commit, generate documents if any docstring has been changed
rm -rf docs
pdoc --html --config show_source_code=False -f -o ./docs sktmls
Version
sktmls package version is automatically genereated followd by a production release on format YY.MM.DD
We use Calendar Versioning. For version available, see the tags on this repository.
1 maintainer
Release files for sktmls 2020.12.16rc43
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| sktmls-2020.12.16rc43.tar.gz | 462.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| sktmls-2020.12.16rc43-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 1.1 MB
Release files / sktmls-2020.12.16rc43.tar.gz
| Download URL | sktmls-2020.12.16rc43.tar.gz |
|---|---|
| Size | 462.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
1262eb5f1cf93aee9213660ca253df4de988f5b5aed0f14a85a69d6facbc59c0
|
|
BLAKE2b-256 checksum How to use checksums |
51e75c54879af70c5799865ed0179b61a1a549f9f9565f52f7750cd1e6b0e4be
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.2.0 pkginfo/1.6.1 requests/2.25.1 setuptools/51.0.0 requests-toolbelt/0.9.1 tqdm/4.54.1 CPython/3.8.6
|
Release files / sktmls-2020.12.16rc43-py3-none-any.whl
| Download URL | sktmls-2020.12.16rc43-py3-none-any.whl |
|---|---|
| Size | 637.6 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
d97f03f6e33cde4ace1d3869e8a3ea222322b30267d3601577aab4d8c1ef82be
|
|
BLAKE2b-256 checksum How to use checksums |
7ddd1948a16d1e4597a1f692483c447e9584ae0373f26b17ccb8e11c29d9b156
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.2.0 pkginfo/1.6.1 requests/2.25.1 setuptools/51.0.0 requests-toolbelt/0.9.1 tqdm/4.54.1 CPython/3.8.6
|
