semvec/pypi-packages huggingface dataset:
deltas 0.7.0
An experimental diff library for generating operation deltas that represent the difference between two sequences of comparable items.
License: MIT

Deltas
======

An open licensed (MIT) library for performing generating deltas (A.K.A sequences
of operations) representing the difference between two sequences of comparable
tokens.

* **Installation:** ``pip install deltas``
* **Repo**: http://github.com/halfak/Deltas
* **Documentation**: http://pythonhosted.org/deltas
* Note this library requires Python 3.3 or newer

This library is intended to be used to make experimental difference detection
strategies more easily available.  There are currently two strategies available:

``deltas.sequence_matcher.diff(a, b)``:
    A shameless wrapper around `difflib.SequenceMatcher` to get it to work
    within the structure of *deltas*.
``deltas.segment_matcher.diff(a, b, segmenter=None)``:
    A generalized difference detector that is designed to detect block moves
    and copies based on the use of a ``Segmenter``.

:Example:
    >>> from deltas import segment_matcher, text_split
    >>>
    >>> a = text_split.tokenize("This is some text.  This is some other text.")
    >>> b = text_split.tokenize("This is some other text.  This is some text.")
    >>> operations = segment_matcher.diff(a, b)
    >>>
    >>> for op in operations:
    ...     print(op.name, repr(''.join(a[op.a1:op.a2])),
    ...           repr(''.join(b[op.b1:op.b2])))
    ...
    equal 'This is some other text.' 'This is some other text.'
    insert ' ' '  '
    equal 'This is some text.' 'This is some text.'
    delete '  ' ''
fnet-flax 0.0.1
Minimal Flax implementation of FNet: Mixing Tokens with Fourier Transforms
License: MIT

![](https://github.com/SauravMaheshkar/FNet-Flax/blob/main/assets/fnet.jpeg?raw=true)

In this [paper](https://arxiv.org/abs/2105.03824), the authors introduce FNet, a new architecture inspired by Transformers where the learnable Self-Attention layer has been replaced by a unlearnable Fourier Transform. This work highlights the potential of linear units as a drop-in replacement for the attention mechanism. They particularly found Fourier Transforms to be an effective mixing mechanism, in part due to the highly efficient FFT. Remarkably, this unparameterized mixing mechanism can yield relatively competitive models. This work among many is particularly important for deploying transformer like models to low-compute scenarios.

## Installation

You can install this package from PyPI:

```sh
pip install fnet-flax
```

Or directly from GitHub:

```sh
pip install --upgrade git+hhttps://github.com/SauravMaheshkar/FNet-Flax.git
```

## Usage

```python
import numpy as np
from jax import random
from fnet_flax import FNet

x = np.random.randn(2, 8, 32)
init_rngs = {"params": random.PRNGKey(0), "dropout": random.PRNGKey(1)}
model = FNet(depth=2, dim=32).init(init_rngs, x)
```

## Development

### 1. Conda Approach

```sh
conda env create --name <env-name> sauravmaheshkar/fnet
conda activate <env-name>
```

### 2. Docker Approach

```sh
docker pull ghcr.io/sauravmaheshkar/fnet-dev:latest
docker run -it -d --name <container_name> ghcr.io/sauravmaheshkar/fnet-dev
```

Use the [Remote Containers](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.remote-containers) Extension in VSCode and [attach to the running container](https://code.visualstudio.com/docs/remote/attach-container). The code resides in the `code/` dir.

Alternatively you can also download the image from [Docker Hub](https://hub.docker.com/r/sauravmaheshkar/fnet-dev).

```sh
docker pull sauravmaheshkar/fnet-dev
```

## Citations

```bibtex
@misc{leethorp2021fnet,
      title={FNet: Mixing Tokens with Fourier Transforms},
      author={James Lee-Thorp and Joshua Ainslie and Ilya Eckstein and Santiago Ontanon},
      year={2021},
      eprint={2105.03824},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
```
pyoppleio 1.0.7
Python library for interfacing with opple mobile control light
License: MIT
Requires Python: >=3.5
Keywords: opple,iot

This library (and its accompanying cli tool) is used to interface with
opple mobile-control lights.

## Supported Devices
All opple light with WIFI support (mobile control)

## Install
```bash
    pip install pyoppleio
```

## API Reference

class **OppleLightDevice**

*property:*
- **is_onlinee** [True|False] Readonly
- **power_on** [True|False] Read/Write
- **brightness** [10-255] Read/Write
- **color_temperature** [2700-6500] Read/Write

*method:*
- **__init__(ip)**
- **update()**

### Demo:
```python
    from pyoppleio.OppleLightDevice import OppleLightDevice
    
    light = OppleLightDevice('192.168.0.222')
    
    if not light.is_online:
        print('light is offline')
    elif not light.power_on:
        light.power_on = True
    else:
        light.brightness = 255
```

## CLI Command
-  search lights
   ```bash
   oppleio search
   ```
-  get one light's status
   ```bash
   oppleio get -a [light ip address]
   ```
-  turn on of turn off one light
   ```bash
   oppleio set -a [device ip address] -p on
   oppleio set -a [device ip address] -p off
   ````
-  set light's brightness and color temperature
   ```bash
   oppleio set -a [device ip address] -b 200 -c 4200
   ```
easy-python 0.2
Easy python is an a simple library to learn python in spanish more happy :D
License: MIT
Keywords: easy-python,learn-easy,python3

# Easy python
This tool is for news in python lenguage programming, the commands are in spanish to help the spanish comunnity

# Functions
This is a beta. Here are the functions

**Console Functions:**<br /> 
- print = consola.escribir('parameters')<br /> 
- input = consola.recibir('input parameters')

**Numbers functions:**<br /> 
- + (sum) = numeros.sumar(number,number,number,etc...) <br /> 
- - (subtract) = numeros.restar(number,number,number,etc...) <br /> 
- * (multiply) = numeros.multiplicar(number,number,number,etc..) <br /> 
- / (divide) = numeros.dividir(arg1, arg2) 'Only you can divide 2 numbers' <br />

**Extra functions:**<br /> 
- Timezone = You can see the Timezone in your pc, you can customize it how this example: "extras.tiempo('%d-%m-%Y %H:%M:%S')" if you dont want to customize it, you can place how this "extras.tiempo()" 


## Future
- New console commands and extras functions!