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 2020.12.16rc39
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-2020.12.16rc39.tar.gz | 462.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| sktmls-2020.12.16rc39-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 1.1 MB
Release files / sktmls-2020.12.16rc39.tar.gz
| Download URL | sktmls-2020.12.16rc39.tar.gz |
|---|---|
| Size | 462.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
60486049824e14b30d10d5a28a131ba108aff144efcc337bbec8465f7cba7c55
|
|
BLAKE2b-256 checksum How to use checksums |
ab36cb19e9e3f27c68a00e5e8245850ba99caebd62f92187a663e3dc7ca8bad4
|
| 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-2020.12.16rc39-py3-none-any.whl
| Download URL | sktmls-2020.12.16rc39-py3-none-any.whl |
|---|---|
| Size | 637.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
c451ab6073b2728cf2c13747e581c0dd546b1abd696f5863da94cdaeaeee75f6
|
|
BLAKE2b-256 checksum How to use checksums |
2f3a6d0846bf03cd17622600c11458b5a4491e27b16b25ce9d444808ee527e6f
|
| 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
|
