semvec/pypi-packages huggingface dataset:
ARIclicker 2.0.1
The best autoclicker in minecraft!
License: MIT
Keywords: autoclicker,minecraft-auto

# **--ARIclicker--** # 


## Runtime Dependencies ##
* python>=3.0



## Requires ##
* pynput
## Installation ##
`
pip install ARIclicker
`

## Function ##
* `def autoclick(start_stop_key_character, end_key_character, button,delay_min, delay_max) `



## Attention ##
* This clicker can reduce the risk of banning to a certain extent, but it does not mean that it can guarantee that it will not be banned!

* Please do not turn on the clicker for a long time! otherwise it may cause some impact on the hardware, in addition, it may increase the risk of banning!



### have fun ~ ###
<br><br>


## Change log ##


 ### **2.0.1**  (2023/7/17): ###
 * Fixed several bugs
 * Remove the "autopress" function
cutters 0.1.4
A rule based sentence segmentation library.
License: MIT

<div align="center">
    <h1>cutters</h1>
    <p>
    A rule based sentence segmentation library.<br>
    <i>Python bindings for the <a href="https://crates.io/crates/cutters">cutters</a> library written in Rust.</i>
    </p>
</div>
<p align="center">
    <a href="https://pypi.org/project/cutters/">
        <img alt="Release" src="https://img.shields.io/pypi/v/cutters">
    </a>
    <a href="https://github.com/cyanic-selkie/cutters/blob/main/LICENSE">
        <img alt="License" src="https://img.shields.io/pypi/l/cutters">
    </a>
    <img alt="Downloads" src="https://img.shields.io/pypi/dm/cutters">
</p>
<p align="center">
🚧 <b>This library is experimental.</b> 🚧
</p>

## Features
- Full UTF-8 support.
- Robust parsing.
- Language specific rules (each defined by its own [PEG](https://en.wikipedia.org/wiki/Parsing_expression_grammar)).
- Fast and memory efficient parsing via the [pest](https://github.com/pest-parser/pest) library.
- Sentences can contain quotes which can contain subsentences.

## Supported languages
- Croatian (standard)
- English (standard)

There is also an additional `Baseline` "language" that simply splits the text on [sentence terminals](https://unicode.org/L2/L2003/03145-sentence-term.htm) as defined by UTF-8. Its intended use is for benchmarking.

## Example

After installing the `cutters` package with `pip`, usage is simple (note that the language is defined via [ISO 639-1](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes) two letter language codes).

```python
import cutters

text = """
Petar Krešimir IV. je vladao od 1058. do 1074. St. Louis 9LX je događaj u svijetu šaha. To je prof.dr.sc. Ivan Horvat. Volim rock, punk, funk, pop itd. Tolstoj je napisao: "Sve sretne obitelji nalik su jedna na drugu. Svaka nesretna obitelj nesretna je na svoj način."
""";

sentences = cutters.cut(text, "hr");

print(sentences);
```

This results in the following output (note that the `str` struct fields are `&str`).
```
[Sentence {
    str: "Petar Krešimir IV. je vladao od 1058. do 1074. ",
    quotes: [],
}, Sentence {
    str: "St. Louis 9LX je događaj u svijetu šaha.",
    quotes: [],
}, Sentence {
    str: "To je prof.dr.sc. Ivan Horvat.",
    quotes: [],
}, Sentence {
    str: "Volim rock, punk, funk, pop itd.",
    quotes: [],
}, Sentence {
    str: "Tolstoj je napisao: \"Sve sretne obitelji nalik su jedna na drugu. Svaka nesretna obitelj nesretna je na svoj način.\"",
    quotes: [
        Quote {
            str: "Sve sretne obitelji nalik su jedna na drugu. Svaka nesretna obitelj nesretna je na svoj način.",
            sentences: [
                "Sve sretne obitelji nalik su jedna na drugu.",
                "Svaka nesretna obitelj nesretna je na svoj način.",
            ],
        },
    ],
}]
```