semvec/pypi-packages huggingface dataset:
mlserving 0.2.0
'A framework for developing a realtime model-inference service.'
License: MIT
Requires Python: >=3.6

# ML Serving
[![PyPI version](https://badge.fury.io/py/mlserving.svg)](https://badge.fury.io/py/mlserving)
[![Build](https://github.com/orlevii/mlserving/workflows/build/badge.svg)]()

**mlserving** is a framework for developing a realtime model-inference service.

Allows you to easily set-up an inference-endpoint for your ML Model.

**mlserving** emphasizes on high performance and allows easy integration with other model servers such as **TensorFlow Serving**

Docs can found here:
https://mlserving.readthedocs.io/en/latest/

## Motivation
Data Scientists usually struggle with integrating their ML-models to production.

**mlserving** is here to make the development of model-servers easy for everyone.

## Installation
```bash
$ pip install mlserving
```
Kickbase-API 0.0.8
Python API library for kickbase
License: MIT

# Kickbase_API
[Kickbase](https://www.kickbase.com/) API for Python 3.  This work is unofficial and not related to kickbase in any way. All of this was done for scientific reasons only and you should not use it for anything else but for your personal learning!

## Installation
- From pypi:
`pip3 install kickbase_api`

## Requirements
- [requests](https://github.com/kennethreitz/requests)

## Usage
```python
from kickbase_api.kickbase import Kickbase
kickbase = Kickbase()
user, leagues = kickbase.login("username", "password")
```

## Docs
The docs for this library can be found [here](https://kevinskyba.github.io/kickbase-api-python/).

## API
This library is based on [Kickbase API Doc](https://github.com/kevinskyba/kickbase-api-doc).

## License

[MIT License](LICENSE.md)
ject 0.0.3
functional extensions
License: MIT
Requires Python: >=3.8,<4.0
Keywords: function,functional,fp,pipe,pipeline,lambda,noop,signature

# ject
#### functional extensions

### Features
- length: get length of function parameters
- oneself: returns the parameter itself
- pipe: pipe chain of functions

### Usage
#### get length of function parameters
```python
from ject import length

def fun(a, b, *args, **kwargs): return a, b, args, kwargs

print(length(fun)) # 4
```

#### pipe chain of functions
```python
from ject import pipe

def add_one(n): return n + 1
def times_two(n): return n * 2

add_one_then_times_two = pipe(add_one, times_two)
print(add_one_then_times_two(4))  # 10
```