semvec/pypi-packages huggingface dataset:
clodius 0.20.4
Tile generation for big data
License: MIT

# Clodius

[![Python](https://img.shields.io/pypi/v/clodius)](https://pypi.org/project/clodius)
[![Build Status](https://travis-ci.org/higlass/clodius.svg?branch=develop)](https://travis-ci.org/higlass/clodius)
[![Docs](https://img.shields.io/badge/docs-📖-red.svg?colorB=6680ff)](https://docs.higlass.io/data_preparation.html)

Displaying large amounts of data often requires first turning it into
not-so-large amounts of data. Clodius is a program and library designed
to aggregate large datasets to make them easy to display at different
resolutions.

## Demo

Install the clodius package:

```shell
pip install clodius
```

And use it aggregate a bigWig file:

```shell
curl https://raw.githubusercontent.com/hms-dbmi/clodius/develop/test/sample_data/geneAnnotationsExonsUnions.short.bed \
  > /tmp/sample.short.bed
clodius aggregate bedfile /tmp/sample.short.bed
```

The output files can then be displayed using [higlass-manage](https://github.com/higlass/higlass-manage). For more information about viewing these types of files take a look at the [higlass docs](https://docs.higlass.io).

[More examples](COMMANDS.md) are available.

## File Types

- Non-genomic Rasters
  - [TSV Files](docs/raster/tsv.rst)
- Genomic Data
  - [Bed Files](docs/genomic/bed.rst)
  - [BedGraph Files](docs/genomic/bedgraph.rst)
  - [Bedpe-like Files](docs/genomic/bedpe.rst)
  - [BigBed Files](docs/genomic/bigbed.rst)
  - [BigWig Files](docs/genomic/bigwig.rst)
  - [Chromosome Sizes](docs/genomic/chromosome-sizes.rst)
  - [Cooler Files](docs/genomic/cooler.rst)
  - [Gene Annotation](docs/genomic/gene-annotation.rst)
  - [HiTile Files](docs/genomic/hitile.rst)
  - [Multivec Files](docs/genomic/multivec.rst)

## Development


The recommended way to develop `clodius` is to use a [conda](https://conda.io/docs/intro.html) environment and
install `clodius` with develop mode:

```shell
pip install -e ".[dev]"
```

## Testing


The unit tests for clodius can be run using [pytest](https://docs.pytest.org/en/latest/):

```shell
pytest
```

Individual unit tests can be specified by indicating the file and function
they are defined in:

```shell
pytest test/cli_test.py:test_clodius_aggregate_bedgraph
```
universal-encryptor 0.1.0
Universal file encryptor and decryptor with GUI
License: MIT
Requires Python: >=3.8

# Universal File Encryptor

A Python GUI tool for encrypting and decrypting files using AES encryption and auto file type detection.

## Features
- AES encryption and decryption
- File type detection using `filetype`
- GUI using CustomTkinter
- Key storage and logging

## Installation
```bash
pip install universal_encryptor
```

## Usage
```bash
python -m universal_encryptor.GUI
```
char_similar_z 0.1.0
计算两个字符的相似度
License: MIT
Requires Python: <=3.13,>=3.10

# char-similar-z
 汉字字形/拼音/语义相似度(单字, 可用于数据增强, CSC错别字检测识别任务(构建混淆集))

- 备注: 完全基于[https://github.com/yongzhuo/char-similar](https://github.com/yongzhuo/char-similar) 项目, 仅修改了部分代码(删除了多线程和多进程，只保留了基础的功能), 使其支持python3.10+版本, 其他功能和使用方式保持一致.



# 一、安装
```bash
pip install char_similar_z
```

# 二、使用方式

## 2.1 详细使用
```python3
import time
from char_similar_z import CharSimilarity

# "shape"-字形; "all"-汇总字形/词义/拼音; "w2v"-词义优先+字形; "pinyin"-拼音优先+字形
# kind = "shape"  # "all"  # "w2v"  # "pinyin"  # "shape"
# 对于字符而言， 使用 w2v 和all 无意义， 推荐使用 pinyin
sim = CharSimilarity()
char1 = "我"
char2 = "他"
for kind in ["shape", "pinyin", "w2v", "all"]:
    t0 = time.time()
    score = sim.std_cal_sim(char1, char2, kind=kind)
    t1 = time.time()
    print(f"相似度({char1}, {char2})[{kind}]: {score}, 用时: {round(t1 - t0, 4)}s")


```





# 三、技术原理
```
char-similar最初的使用场景是计算两个汉字的字形相似度(构建csc混淆集), 后加入拼音相似度,字义相似度,字频相似度...详见源码.

# 四角码(code=4, 共5位), 统计四个数字中的相同数/4
# 偏旁部首, 相同为1
# 词频log10, 统计大规模语料macropodus中词频log10的 1-(差的绝对值/两数中的最大值)
# 笔画数, 1-(差的绝对值/两数中的最大值)
# 拆字, 集合的与 / 集合的并
# 构造结构, 相同为1
# 笔顺(实际为最小的集合), 集合的与 / 集合的并
# 拼音(code=4, 共4位), 统计四个数字中的相同数(拼音/声母/韵母/声调)/4
# 词向量, char-word2vec, cosine
```


# 四、参考(部分字典来源以下项目)
 - [https://github.com/contr4l/SimilarCharacter](https://github.com/contr4l/SimilarCharacter)
 - [https://github.com/houbb/nlp-hanzi-similar](https://github.com/houbb/nlp-hanzi-similar)
 - [https://github.com/mozillazg/python-pinyin](https://github.com/mozillazg/python-pinyin)
 - [https://github.com/CNMan/UnicodeCJK-WuBi](https://github.com/CNMan/UnicodeCJK-WuBi)
 - [https://github.com/yongzhuo/Macropodus](https://github.com/yongzhuo/Macropodus)
 - [https://github.com/kfcd/chaizi](https://github.com/kfcd/chaizi)
 


# Reference
For citing this work, you can refer to the present GitHub project. For example, with BibTeX:
```
@misc{Macropodus,
    howpublished = {https://github.com/yongzhuo/char-similar},
    title = {char-similar},
    author = {Yongzhuo Mo},
    publisher = {GitHub},
    year = {2024}
}
```
buildsnap 0.2.1
Snap together Python package builds and init
License: MIT
Requires Python: >=3.6

# BuildSnap

**BuildSnap** is a Python CLI tool that helps you easily build and init Python packages using `setup.py`. It's simple, fast and cool.

## Features

- Build `.tar.gz` (source) and `.whl` (wheel) distributions
- Make a ready setupped package directory and files
- Lightweight and terminal-friendly

## Commands

```bash
buildsnap --help

buildsnap build
options:
--tar, --whl
--path, -p

Example:
buildsnap build --tar -p /sdcard/mypkg

buildsnap init
options
--name
--username

Example:
buildsnap init --name MyPKG --username User

buildsnap install
options:
--path, -p

Example:
buildsnap install --path /sdcard/MyPKG
```

## Installation

```bash
pip install buildsnap
```