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Maisie-0.1.6
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مشاهده بیشترتوضیحات
User-oriented system for painless managing, storing, sharing, organizing and deploying Machine Learning models.
| ویژگی | مقدار |
|---|---|
| سیستم عامل | OS Independent |
| نام فایل | Maisie-0.1.6 |
| نام | Maisie |
| نسخه کتابخانه | 0.1.6 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Zofia Kochutek, Łukasz Kleczaj, Marek Kochanowski |
| ایمیل نویسنده | support@maisie.dev |
| آدرس صفحه اصلی | https://github.com/nokia-wroclaw/innovativeproject-ml-models-management |
| آدرس اینترنتی | https://pypi.org/project/Maisie/ |
| مجوز | MIT |
Maisie - ML Models Management System
####################################
.. |RTFD_BADGE| image:: https://img.shields.io/readthedocs/maisie.svg
:alt: Read the Docs Badge
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:alt: DockerHub Pulls Badge
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| `Documentation <https://docs.maisie.dev>`_ | |RTFD_BADGE| |
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| `PyPI <https://pypi.org/project/Maisie/>`_ | |PyPI_Badge| |
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| `DockerHub <https://hub.docker.com/r/maisiedev/maisie>`_ | |DockerHub_Badge| |
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.. contents:: \
.. section-numbering::
Features
========
Could archiving, storing, managing and organizing machine learning models be done efficiently and with great focus on user experience? Sure, Maisie does just that.
Maisie is a friendly, easy to use assistant that consists of:
- Web Application written in React
- Backend API written in Python, Flask
- Client Application/Package written in Python and hosted on PyPI
It integrates seamlessly with your favorite tools and provides you with all the important data, such as:
- Git revisions for all trained models, as well as information about source branches
- Searchable, filterable hyperparameters, parameters and metrics
- A single identifying dataset name, as well as an optional description
- Permanent URLs for easy sharing and downloading of stored models
Installing
==========
You can get the most current package from `PyPI <https://pypi.org/project/Maisie/>`_
.. code-block:: bash
$ pip install Maisie
Using it in your training environment is fairly straightforward:
.. code-block:: python
import maisie
from sklearn.externals import joblib
# Define your model here
model.fit(X, y)
model_filename = "example_model.pkl"
joblib.dump(model, model_filename)
# Define your metrics, fetch parameters and hyperparameters
models = maisie.Models()
models.upload(
name="My first uploaded model",
filename=model_filename,
dataset_name="Singly Identifying Dataset Name",
metrics={"accuracy": accuracy},
hyperparameters=hyperparameters,
parameters=parameters,
)
Deploying
=========
Using docker-compose
--------------------
This repository provides a pre-configured ``docker-compose.yml`` file that contains sensible default options.
Before starting the containers, you should create a local ``.env`` file using the included ``.env.sample``.
To start up all services, run:
.. code-block:: bash
$ docker-compose up
To stop your services, you can press Ctrl+C/Ctrl+D. If you started the services in the background using ``docker-compose up -d``, the correct way to do this would be:
.. code-block:: bash
$ docker-compose stop
You can learn more about Docker Compose by `clicking here <https://docs.docker.com/compose/>`_.
Fetching individual images
--------------------------
Both frontend and backend images are automatically published to `Docker Hub <https://hub.docker.com>`_ as soon as new stable release is made available.
Links
- `Frontend image on Docker Hub <https://hub.docker.com/r/kochanowski/maisie>`_
- `Backend image on Docker Hub <https://hub.docker.com/r/kochanowski/maisie>`_
- ...other services
For reference, you can look at the `sample Ansible playbook <#>`_ that deploys all containers to a specified host using the locally configured ``.env`` file.
Contributing
============
Getting started
---------------
1. Clone the repository from the ``develop`` branch
.. code-block:: bash
$ git clone -b develop git@github.com:nokia-wroclaw/innovativeproject-ml-models-management.git
2. Install `pre-commit <https://pre-commit.com/#install>`_
3. Inside the project's root directory install all required githooks:
.. code-block:: bash
$ pre-commit install
4. To start all required services for local development, run:
.. code-block:: bash
$ docker-compose up
5. You're all set up!
Fixing existing issues
----------------------
1. Pick one of the `open issues <https://github.com/nokia-wroclaw/innovativeproject-ml-models-management/issues>`_ or `create a new one <https://github.com/nokia-wroclaw/innovativeproject-ml-models-management/issues/new>`_
2. Create a new branch named ``issue-[number]-[short description]`` derived from the ``develop`` branch, for example
.. code-block:: bash
$ git checkout -b issue-42-project-removal-permissions develop
3. Make sure your implementation fixes the actual problem and is well tested.
Implementing new features
-------------------------
When implementing new features, you should start by creating a new branch named ``feature-[short description]`` derived from the ``develop`` branch, for example
.. code-block:: bash
$ git checkout -b feature-new-user-profile develop
Commiting the changes
---------------------
To run all tests and check whether all required pre-commit githooks are satisfied, run
.. code-block:: bash
$ pre-commit run --all-files
Your commit message should briefly summarize the changes (if possible) in plain English. To learn how to write a proper commit message, check out `this article <https://juffalow.com/other/write-good-git-commit-message>`_.
When ready, create a new pull request compared with the ``develop`` branch set as a base branch.
Documentation
=============
For the lastest stable release, the documentation can be seen at `docs.maisie.dev <https://docs.maisie.dev>`_.
نیازمندی
| مقدار | نام |
|---|---|
| >=7.0 | Click |
| >=2.1.1 | gitpython |
| >=2.22.0 | requests |
| >=10.0 | coloredlogs |
| >=5.1.1 | pyyaml |
| >=3.1.0 | terminaltables |
| >=0.0.93 | ago |
| >=2.8.0 | python-dateutil |
نحوه نصب
نصب پکیج whl Maisie-0.1.6:
pip install Maisie-0.1.6.whl
نصب پکیج tar.gz Maisie-0.1.6:
pip install Maisie-0.1.6.tar.gz