semvec/pypi-packages huggingface dataset:
dataqualityx 0.1.2
data quality

# DataQuality
[![Total Lines](https://tokei.rs/b1/github/zzzzzzzs/DataQuality?category=lines)](https://github.com/zzzzzzzs/DataQuality)

## 快速开始
```shell
pip install dataqualityx
```
多文件任务
```shell
dataqualityx --files C:\warehouse\user\task
```
单文件任务
```shell
dataqualityx --files C:\warehouse\user\task\dws_test.yaml
```

## 脚本编写
```yaml
db:
  type: doris
  host: "127.0.0.1"
  port: 9030
  user: "admin"
  pw: "xxx"
  db: "ods"
vars:
  - var: "${dt} = $[yyyy-MM-dd-1]"
tasks:
    - task:
      sql: |
        -- 校验 dws_test 表中前一天的数据是否存在
        select count(1) from dws.dws_test
        where dt = '${dt}'
      expected:
        - row: "> 0"
      alert:
    - task:
      sql: |
        -- 校验 dws_test 表中4种类型是否存在数据
        select count(1)
        from dws.dws_test
        where dt = '${dt}'
        group by type
        order by type
      expected:
        - row: "> 0"
        - row: "> 0"
        - row: "> 0"
        - row: "> 0"
      alert:
```

## 支持命令
- `--files /home/users/xxx` : 支持指定文件路径 (必填)
- `--alerts none` : 支持全局禁止报警

## 支持数据库
- [x] mysql
- [x] doris
- [ ] hive
- [ ] clickhouse
- [ ] clickhouse
- [ ] postgresql
easy-logs 1.1.2
package for easy colored logs with predefined configurations.
Requires Python: >=3.8


![example workflow](https://github.com/michalskibinski109/easy_logs/actions/workflows/python-app.yml/badge.svg)
[![PyPI version](https://badge.fury.io/py/easy_logs.svg)](https://badge.fury.io/py/miskibin)
[![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit)](https://github.com/pre-commit/pre-commit)
# easy_logs
[Documentation](https://github.com/michalskibinski109/easy_logs/tree/main#readme)
nfonistax 0.2
• instagram profile info
Requires Python: >=3.8

<h1 align="center">ALAA7X</h1>
<p align="center">instagram profile info</p>

<p align="center"> • DevVlopered The Lib BY 3laa</p>


## Installing :
```
pip install nfonistax

```
fro
a=info("user")
print(a)
```
chatgpt-Cloud 0.5.5
A package for Pandora-ChatGPT
Requires Python: >=3.7
Keywords: OpenAI ChatGPT ChatGPT-Plus

# Pandora-Cloud

![Python version](https://img.shields.io/badge/python-%3E%3D3.7-green)
[![Issues](https://img.shields.io/github/issues-raw/pengzhile/pandora-cloud)](https://github.com/pengzhile/pandora-cloud/issues)
[![Commits](https://img.shields.io/github/last-commit/pengzhile/pandora-cloud/master)](https://github.com/pengzhile/pandora-cloud/commits/master)
[![PyPi](https://img.shields.io/pypi/v/pandora-cloud.svg)](https://pypi.python.org/pypi/pandora-cloud)
[![Downloads](https://static.pepy.tech/badge/pandora-cloud)](https://pypi.python.org/pypi/pandora-cloud)

[![PyPi workflow](https://github.com/pengzhile/pandora-cloud/actions/workflows/python-publish.yml/badge.svg)](https://github.com/pengzhile/pandora-cloud/actions/workflows/python-publish.yml)

### A package for Pandora-ChatGPT
sidechannelattack 0.0.2
sidechannelattack

Alignment principle: the reference curve l_0 is selected and the rest of the curve l_i is aligned towards l_0, using the pattern matching method.
Dimensionality reduction principle: PCA dimensionality reduction
Filtering principle: open source package signal: low-pass, band-pass, high-pass. Own implementation of fast filtering.
nb.jit is different from nb.cuda.jit and should be distinguished
When the amount of data is large, it should be stored in blocks and the corresponding side channel processing method should consider how to process it block by block.
pishockpy 0.0.4
Control a PiShock via the API.
Keywords: pishock

# pishockpy

Comfortably use the [PiShock](https://PiShock.com) API in Python.  
This requires at least `Python 3`

## Usage
Import the package:
```python
from pishockpy import PishockAPI
```
Declare a new shocker instance:
```python
pishock = PishockAPI("YOUR_API_KEY", "YOUR_USERNAME", "SHARECODE", "YOUR_APP_NAME")
```
Run actions on a shocker:
```python
# Send a shock - intensity (float between 0 and 1) and duration in seconds (integer between 1 and 15)
pishock.shock(INTENSITY, DURATION)

# Send a mini shock - intensity (float between 0 and 1)
pishock.minishock(INTENSITY)

# Send a vibration - intensity (float between 0 and 1) and duration in seconds (integer between 1 and 15)
pishock.vibrate(INTENSITY, DURATION)

# Send a sound - duration in seconds
pishock.beep(DURATION)

```

Check if an action was successful:
```python
if(pishock.shock(INTENSITY, DURATION)):
    print("Shock was successful")
else:
    print("Shock was not successful")
```

### Disclaimer
I'm not affiliated with PiShock in any way. I am also not responsible for any damage caused by this library.
mount-azure-blob 0.0.7
Mount Azure blob storage in google colab.
Requires Python: >=3.7

# Mount Azure Blob Storage in Colab

## How to use 
### Approch 1
```
from mount_azure_blob import mount_storage
mount_storage(mount_path="blob-storage", config_file=None)
```
output: 
![image](https://user-images.githubusercontent.com/58617251/222134815-9404dd84-8fb4-46c5-8919-e1c77748abfe.png)
Enter the credentials and click ```Mount Storage``` button

### Approch 2
```
from mount_azure_blob import mount_storage
mount_storage(mount_path="blob-storage", config_file="path-to-.env-file")
```
#### sample ```config_file``` / ```.env```
```
accountName ...
accountKey ...
containerName ...
```
output: 

![image](https://user-images.githubusercontent.com/58617251/222144492-88eebbfa-4e91-48c6-acec-950f2bf7b799.png)

### After mount
![image](https://user-images.githubusercontent.com/58617251/222145707-28b625a6-a1f0-479c-9748-e7ad69a18fa3.png)


## Reference

[Blobfusev1 official document](https://learn.microsoft.com/en-us/azure/storage/blobs/storage-how-to-mount-container-linux)