semvec/pypi-packages huggingface dataset:
PyWeekends 0.0.2
A simple Python Weekends lib
License: MIT
Requires Python: >=3.9

# PyWeekends: Weekend Dates Formatter

PyWeekends is a Python package that provides a convenient way to generate weekend dates based on the Calendar. 
It includes a class named `Weekend` to generate weekend dates and an `OutputFormatter` class to format 
the generated dates into JSON.

## Features

- Generate weekend dates for all months in a given year.
- Generate weekend dates for a specific month.
- Format the generated dates as JSON.

## Installation

To install the package, use pip:

```bash
pip install PyWeekends
```
## Usage
```python
from PyWeekends import Weekend, WeekendStart

# Generate weekend dates for a specific month and format as JSON
w = Weekend(year=2024)
january_weekends = w.month_weekends("January")
json_data = january_weekends.as_json()
print(json_data)
# Output
# ["6", "7", "13", "14", "20", "21", "27", "28"]
# Generate weekend dates for all months and format as JSON
all_month_weekends = w.all_weekends()
json_data_all_months = all_month_weekends.as_json()
print(json_data_all_months)

#Output
# {"1": ["6", "7", "13", "14", "20", "21", "27", "28"], "2": ["3", "4", "10", "11", "17", "18", "24", "25"], 
# "3": ["2", "3", "9", "10", "16", "17", "23", "24", "30", "31"], "4": ["6", "7", "13", "14", "20", "21", "27", "28"], 
# "5": ["4", "5", "11", "12", "18", "19", "25", "26"], "6": ["1", "2", "8", "9", "15", "16", "22", "23", "29", "30"],
# "7": ["6", "7", "13", "14", "20", "21", "27", "28"], "8": ["3", "4", "10", "11", "17", "18", "24", "25", "31"], 
# "9": ["1", "7", "8", "14", "15", "21", "22", "28", "29"], "10": ["5", "6", "12", "13", "19", "20", "26", "27"], 
# "11": ["2", "3", "9", "10", "16", "17", "23", "24", "30"], "12": ["1", "7", "8", "14", "15", "21", "22", "28", "29"]}

```

## Changelog
See [Changelog](CHANGELOG.md)

## License
[MIT](LICENSE)
devo-mlmodelmanager 1.6.1
A client for Devo's ML model manager
License: MIT
Requires Python: >=3.7,<4.0

![License](https://img.shields.io/github/license/DevoInc/python-mlmodelmanager-client)
![Release](https://img.shields.io/github/v/release/DevoInc/python-mlmodelmanager-client?display_name=tag&sort=semver)
![Tests](https://github.com/DevoInc/python-mlmodelmanager-client/actions/workflows/test-tox.yml/badge.svg)
![Python](https://img.shields.io/pypi/pyversions/devo-mlmodelmanager)

# Devo Python ML Model Manager Client

The **ML Model Manager** is a service to register machine learning models on
[Devo](https://www.devo.com) platform. These models can be used through the
query engine using the `mlevalmodel(...)`  operation or through the
[FLOW](https://docs.devo.com/space/latest/95213164/Flow) correlation engine
including in the context the
[MlSingleModelEval](https://docs.devo.com/space/latest/95214962/ML+Single+Model+Evaluator)
unit.

**devo-mlmodelmanager** provides an easy-to-use client for Devo’s ML Model
Manager. Built on top of the widely used
[Requests](https://requests.readthedocs.io/en/latest/) library exposes a
simplified interface for model management, allowing you to focus in the machine
learning workflows and not worry about the integration with Devo platform.

## A simple example

``` python
from devo_ml.modelmanager import create_client_from_token

url = "<model-manager-server-url>"
token = "<valid-access-token>"

client = create_client_from_token(url, token)

client.add_model(
   "pokemon_onnx_regression",          # model name
   "ONNX",                             # model engine
   "~/models/pokemon.onnx",            # model file
   description="A funny Pokemon prediction"
)
```

## Requirements

* Python 3.7+

## Install

``` console
$ pip install devo-mlmodelmanager
```

## Documentation

Explore the [documentation](https://devoinc.github.io/python-mlmodelmanager-client/) to learn more.