semvec/pypi-packages huggingface dataset:
splitn 3.3.0
splitn is a CLI application that generates combinations of chars being a result of splitting strings
License: MIT
Requires Python: >=3.11,<4.0

`splitn` is a CLI application that generates combinations of chars being a result of splitting strings provided *explicite* or randomly generated from regex patterns. It is made mainly for testing NLU applications, e.g. chatbots or tools for extracting structural data from text like [duckling](https://github.com/facebook/duckling).

# Installation
```
pipx install splitn
```

or

```
pip install splitn
```

# Examples
## Basic usage
```bash
$ splitn 486
486
48 6
4 86
4 8 6
```

## Using with regular expressions
```bash
$ splitn "\d{3"
427
4 27
42 7
4 2 7
```

## Using with file
Let's assume that file `example.txt` contains following lines.
```
abc
\d{2}
```

```bash
$ splitn example.txt
abc
a bc
ab c
a b c
---
04
0 4
```

## Options
### --separator
```bash
$ splitn abc -s -
abc
a-bc
ab-c
a-b-c
```

### --times
```bash
$ splitn "\d{2}" -t 2
59
5 9

35
3 5
```

### --secondary-separator
```bash
$ splitn abc def --secondary-separator +++
abc
a bc
ab c
a b c
+++
def
d ef
de f
d e f
```

### --as-string
```bash
$ splitn "\d{2}" --as-string
\d{2}
\ d{2}
\d {2}
\d{ 2}
\d{2 }
\ d {2}
\ d{ 2}
\ d{2 }
\d { 2}
\d {2 }
\d{ 2 }
\ d { 2}
\ d {2 }
\ d{ 2 }
\d { 2 }
\ d { 2 }
```

### --pattern
This option can be used with or without positional arguments. When used without, it makes splitn generate random sequences based on given regular expressions. When used with operands, it narrows down generated sequences to those matching provided regular expressions.

```bash
$ splitn -p "\d \d .{2}"
8 1 Ua
```

```bash
$ splitn "\d{4}" -p "\d \d .*"
5 9 20
5 9 2 0
```
zaya 1.0.5
zaya Library
License: MIT
Keywords: zaya,zaya.io,tousanco



``zaya`` is a toolbox for the https://zaya.io community.


Install
-------

    pip3 install zaya


Usage
-------------

    import zaya


Connect
-------------

    zaya.connect('YourToken')
    # https://zaya.io/developers/api


account details

    zaya.account()


urls

    zaya.create_url('url')
    zaya.all_url()
    zaya.detail_url(id)
    zaya.update_url(id, 'url')
    zaya.delete_url(id)


domains

    zaya.all_domain()
    zaya.create_domain('domain')
    zaya.details_domain(id)
    zaya.update_domain(id, 'domain')
    zaya.delete_domain(id)


subjects

    zaya.subjects()
    zaya.create_subject('name', 'red')
    zaya.details_subject(id)
    zaya.update_subject(id, 'subject')
    zaya.delete_subject(id)


stats

    zaya.clicks(id)
    zaya.stats(id)
    zaya.referrers(id)
    zaya.countries(id)
    zaya.languages(id)
    zaya.browsers(id)
    zaya.devices(id)
    zaya.os(id)


get Information from zaya
-------

    zaya.__version__
    zaya.__author__
    zaya.__website__
    zaya.__documentation__
connectorapipy 2.0
# Projet de Sauvegarde de Données sur Cloud avec PyPy
License: MIT

# Projet de Sauvegarde de DonnÃ©es sur Cloud avec PyPy

## Introduction

Ce projet utilise PyPy, un interprÃ¨te Python Ã  haute performance, pour faciliter la sauvegarde rapide et sÃ©curisÃ©e des donnÃ©es sur un service de cloud Ã  distance. Il est conÃ§u pour Ãªtre simple Ã  configurer et Ã  utiliser, mÃªme pour ceux qui n'ont pas une grande expÃ©rience avec les services cloud ou PyPy.

## CaractÃ©ristiques

- **Haute performance** : grÃ¢ce Ã  PyPy, bÃ©nÃ©ficiez d'une exÃ©cution du script plus rapide par rapport Ã  l'interprÃ¨te Python standard.
- **SÃ©curitÃ©** : toutes les communications avec le service cloud sont sÃ©curisÃ©es.
- **CompatibilitÃ©** : fonctionne avec divers services de stockage cloud, y compris AWS S3 et Google Cloud Storage.

## PrÃ©requis

Avant de commencer, assurez-vous de satisfaire aux prÃ©requis suivants :

- **PyPy** : Installez la derniÃ¨re version de PyPy (version 3.x recommandÃ©e). [Voir la documentation de PyPy pour les instructions d'installation](https://www.pypy.org/)
- **Service cloud** : Un compte sur un service de cloud pris en charge (comme AWS S3 ou Google Cloud Storage) est nÃ©cessaire.

## Installation

1. **Clonage du rÃ©pertoire** : Clonez ce rÃ©pertoire sur votre machine locale :
   
   ```sh
   git clone https://github.com/votre-repo/projet-pypy-sauvegarde-cloud.git
hrmes-python 0.1.0
Demo library
License: MIT

# HRMES
A consistency-preserving api of the HRMES storage model (Highly Reliable Mobile Edge Storage).
It offloads the mission-critical stateful applications to the edge and ensures the reliable tail latency and strong consistency guarantees.

### Installation
```
pip install hrmes-python
```

### Get started
How to create the section:
 
```Python
# import hrmes-python as hrmes
# Prepare the url and port of the server you'd like to connect to 
# And give the keys of data that you want to cache as a parameter
url = "url"
port = 1337
keys = ["a-key", "b-key"]
# id = hrmes.create_section(url, port, keys)
```
How to access to the cache:
```Python
# Read the data from the cache
key = "a-key"
# hrmes.read_data(id, key)

value = "a-new-value"
# write the data to the cache
# hrmes.write_data(id, key, value)
```
How to commit the updates to the server:
```Python
# Read the data from the cache
# hrmes.commit(id)
```