semvec/pypi-packages huggingface dataset:
dinarlib 0.0.2
This library simplifies the code
Requires Python: >=3.6
Keywords: dinar quick_sort intersec

# DinarLib #
## What is this? ##

This library simplifies the code

## Intersec ##

A method for finding intersections of an array

    def intersec(a,b):
    c = []
    for element in a:
        if element in b:
            c.append(element)
    return len(c)

## Quick_sort ##

The most optimized array sorting

    def partition(sort_nums, begin, end):
    part = begin
    for i in range(begin+1, end+1):
        if int(sort_nums[i][4]) <= int(sort_nums[begin][4]):
            part += 1
            sort_nums[i], sort_nums[part] = sort_nums[part], sort_nums[i]
    sort_nums[part], sort_nums[begin] = sort_nums[begin], sort_nums[part]
    return part
    def quick_sort(sort_nums, begin=0, end=None):
        if end is None:
            end = len(sort_nums) - 1
        def quick(sort_nums, begin, end):
            if begin >= end:
                return
            part = partition(sort_nums, begin, end)
            quick(sort_nums, begin, part-1)
            quick(sort_nums, part+1, end)
        return quick(sort_nums, begin, end)

## Random_sum ##

The maximum and the sum of the numbers are accepted as input
Allows you to randomly collect numbers in an array that will equal the amount specified in the parameter

    def random_sum(n, num_terms = None):
        num_terms = (num_terms or random.randint(2, n)) - 1
        a = random.sample(range(1, abs(n)), num_terms) + [0, abs(n)]
        list.sort(a)
        return [a[i+1] - a[i] for i in range(len(a) - 1)]

## Developer ##

https://github.com/ShakhmametovDinar
celltraj-copperma 0.1.0
Toolset for single-cell trajectory modeling.
Requires Python: >=3.5

celltraj
========

[![image](https://img.shields.io/pypi/v/celltraj.svg)](https://pypi.python.org/pypi/celltraj)

[![image](https://img.shields.io/travis/jcopperm/celltraj.svg)](https://travis-ci.com/jcopperm/celltraj)

[![Documentation Status](https://readthedocs.org/projects/celltraj/badge/?version=latest)](https://celltraj.readthedocs.io/en/latest/?version=latest)

A toolset for single-cell trajectory modeling.

-   Free software: MIT license
-   Documentation: <https://jcopperm.github.io/celltraj>.
-   Morphodynamical Trajectory Embedding tutorial:
    <https://github.com/jcopperm/celltraj/blob/main/tutorials/trajectory_embedding.ipynb>

Features
--------

-   TODO

Credits
-------

This package was created with
[Cookiecutter](https://github.com/audreyr/cookiecutter) and the
[audreyr/cookiecutter-pypackage](https://github.com/audreyr/cookiecutter-pypackage)
project template.
translation-god 1.0.2
A translation tool based ChatGPT
Requires Python: >=3.5

# Translation God

Translation God是一个基于ChatGPT的翻译工具。
可以将一个目录下的所有json文件翻译成指定的语言，并按照原始的文件目录结构生成翻译结果。也可以是单个的javascrit文件，只是必须保证js文件的内容格式如下：

``` javascript
export default {
    "key": "value",
    "key2": "value2"
}
```

如果你想用人工翻译，可以将目录下的json文件借助TranslationGod生成一个Excel文件。
Excel文件经过人工翻译完成之后，可以再次借助TranslationGod将Excle文件翻译写入到各个对应语言的目录中，依然是和源语言的目录结构保持一致。

## Install
因为包没有推送到仓库中，所以安装的第一步，需要下载源码tar包，并解压，
进入包目录，会看到setup.py这个文件，安装TranslationGod执行如下命令：

``` bash
pip setup.py install
```
安装成功之后，我们在终端执行 `tg -h` 查看tg的一些参数和使用帮助

## Usage

设置`OPENAI_API_KEY`环境变量

``` bash
export OPENAI_API_KEY="sk-xxxxxxx"
```

### 翻译目录下的JSON文件或者翻译单个JSON文件

``` bash
tg --command=tj --sourcelang="Chinese"  --targetlangs="English,Japanese,French" --input="./jsondirectory_or_file" --output="./output"
# or
tg -c tj -s Chinese -t "English,Japanese,French" -i "./jsondirectory" -o "./output"
```

### 翻译Excel文件

``` bash
tg --command=te --sourcelang="Chinese" --input="./my_excel.xlsx" --output="./my_translated_excel.xlsx"

# Or

tg -c te -s Chinese -i "./my_excel.xlsx" -o "./my_translated_excel.xlsx"
```

### 将目录下的JSON文件转换成Excel文件

``` bash
# this command will produce 2 files, one is output option specified, such as "result.xlsx", the other one is "result.map.xlsx"
tg --command=cje --sourcelang="Chinese" --targetlangs="English,Japanese,French" --input="./json_file" --output="./must_end_with_xlsx.xlsx"

# Or

tg -c cje -s "Chinese" -t "English,Japanese,French" -i "./json_file" -o "must_end_with_xlsx.xlsx"
```

### 将Excel的文件转换成对应翻译语言的目录和JSON文件

注意：excel文件必须保持TranslationGod生成的格式。 .map.xlsx文件存储的key，当没有.map.xlsx文件时，将xlsx的第一列作为key

``` bash
# this command will convert result.xlsx and result.map.xlsx to json files
tg --command cej --input "./result.xlsx" --output "outputdir/"

# Or

tg -c cej -i "./result.xlsx" -o "outputdir/"
```

### Generate missing translation entries and output the results to the specified directory


``` bash
tg --command gld --input <lang_dir_or_file> --source <source_lang> --targetlangs="English,Japanese,French" --output <output_langs_dir>

# or

tg -c gld -i <lang_dir_or_file> -s <source_lang> -t "English,Japanese,French" -o <output_langs_dir>
```


## Merge json files in <input_path> to <target_path>

``` bash
tg --command mj --input <input_dir> --output <output_dir>

# or

tg -c mj -i <input_dir> -o <output_dir>
```


### Insert or Update translation entry

``` bash
tg --command=upsert --input <file> --key <key>   --value <value>

# or

tg -c upsert -i <file> -k <key> -v <value>
```
crawlnet 0.0.9
CrawlNet
Keywords: python

`!pip install crawlnet`

```
from crawlnet.cl3 import Writer

write = Writer('output.txt')
print(write.questions)

write.getCode('Deap')
```

```
from crawlnet.cl4 import Writer

write = Writer('output.txt')
print(write.questions)

write.getCode('convolutional_gan')
```
successive-romaji 0.1.1
Add your description here
Requires Python: >=3.8

# successive_romaji

Returns the input up to that point, the characters currently being input, and the romaji expected in the future, based on the target hiragana sequence and the romaji input up to the halfway point.
Used to implement a typing game.

## Usage

Just use `parse_hiragana_with_buf(hiragana, romaji)`.

## Python bindings

This crate has Python bindings. Source is in ./python/ .

See https://pypi.org/project/successive-romaji/ .

### Build and publish Python binding

```commandline
docker run --rm -v $(pwd):/io ghcr.io/pyo3/maturin build --release -i python3.12 --sdist
rye publish ./target/wheels/*
```