# mls-model-registry (sktmls)
## Contents
- [Description](#description)
- [How to use](#how-to-use)
- [Development](#development)
- [Requirements for development](#requirements-for-development)
- [Local model registry](#local-model-registry)
- [Python environment](#python-environment)
- [Documents generation](#documents-generation)
- [Version](#version)
## 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,
```bash
# 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.
```bash
$ cd ~/
$ mkdir models
```
### Python environment
First you need to do the followings
```bash
$ python -V # Check if the version is 3.6.
$ python -m venv env # Create a virtualenv.
$ . env/bin/activate # Activate the env.
$ 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
```bash
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](https://calver.org). For version available, see the [tags on this repository](https://github.com/sktaiflow/mls-model-registry/releases).
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sktmls-2020.11.4rc22.tar.gz (95个子文件)
sktmls-2020.11.4rc22
PKG-INFO 3KB
sktmls.egg-info
PKG-INFO 3KB
requires.txt 179B
SOURCES.txt 4KB
top_level.txt 7B
dependency_links.txt 1B
setup.cfg 38B
sktmls
models
automl
automl_prediction.py 12KB
__init__.py 524B
mls_model.py 5KB
__init__.py 511B
ml_model.py 45KB
contrib
info_defect_rule_model.py 733B
sample_model.py 806B
mbr_interest_all_baseline_model.py 5KB
default_model.py 2KB
random_score_model.py 3KB
sample_generic_model.py 943B
mbr_valid_category_baseline_model.py 4KB
fee_no_equip_single_emb_model.py 13KB
mbr_popular_benefit_model.py 6KB
mbr_vip_info_rule_model.py 693B
lightgbm_random_context_model.py 4KB
shuffle_list_model.py 4KB
tests
test_lightgbm_random_context_models.py 3KB
test_info_unpaid_rule_models.py 609B
test_vas_xcloud_rule_models.py 3KB
test_mbr_vip_info_rule_models.py 800B
test_tw_random_greeting_rule_model.py 1KB
test_mbr_boostpark_baseline_model.py 4KB
test_mbr_valid_category_baseline_models.py 4KB
test_fee_no_equip_single_emb_models.py 6KB
test_mbr_popular_benefit_model.py 14KB
test_mbr_interest_all_baseline_models.py 5KB
__init__.py 13B
test_info_defect_rule_models.py 1KB
test_random_pick_models.py 3KB
test_mbr_similar_benefit_models.py 11KB
test_shuffle_list_models.py 1KB
test_mbr_custom_benefit_random_model.py 2KB
test_bnf_loyalty_rule_models.py 605B
test_generic_context_models.py 3KB
test_random_score_models.py 963B
test_models.py 85B
test_mbr_category_baseline_models.py 3KB
vas_xcloud_rule_model.py 2KB
bnf_loyalty_rule_model.py 613B
__init__.py 2KB
mbr_similar_benefit_model.py 6KB
mbr_custom_benefit_random_model.py 5KB
sample_rule_model.py 914B
info_unpaid_rule_model.py 580B
tw_random_greeting_rule_model.py 3KB
random_pick_model.py 4KB
mbr_category_baseline_model.py 4KB
generic_context_model.py 19KB
mbr_boostpark_baseline_model.py 4KB
mls_env.py 980B
data_status
__init__.py 145B
status.py 7KB
config
__init__.py 3KB
dynamodb
dynamodb.py 4KB
__init__.py 67B
model_registry.py 12KB
profiles
__init__.py 84B
profile.py 11KB
mls_client.py 4KB
ml_features
ml_feature.py 8KB
__init__.py 96B
__init__.py 357B
apis
profile_api.py 6KB
conversion_tracking_api.py 5KB
__init__.py 271B
recommendation_api.py 5KB
meta_tables
meta_table.py 21KB
__init__.py 117B
dimensions
dimension.py 14KB
__init__.py 94B
experiments
__init__.py 143B
experiment.py 25KB
components
__init__.py 94B
component.py 8KB
filters
__init__.py 79B
filter.py 8KB
clients
client.py 6KB
__init__.py 79B
utils
__init__.py 109B
filter.py 2KB
logic.py 8KB
datasets
dataset.py 13KB
__init__.py 182B
channels
__init__.py 84B
channel.py 9KB
setup.py 1KB
README.md 2KB
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