semvec/pypi-packages huggingface dataset:
pandas-utils-pkg 0.0.1
A helper tool for pandans and mysql
Requires Python: >=3.8

# pandas-utils-pkg
An open source library for pandas and MySQL/MariaDB.

## Prerequisite
Before you get started with the application code, here are some general tips and notes.

To work on this project, you will need : 
- **Docker** for the development environment.
- a text editor. **We strongly recommend that you use VsCode**. Indeed, the project uses Vscode's devcontainer which allows us to work in a Docker environment while having VsCode auto-completion.

## Installation
Once Docker and VsCode are installed, if not already installed, you can download the [Remote Development extension for VsCode](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). This extension will allow you to build and then launch the project.

## Good to know
You will note that our project is currently in alpha. We already use this library on our internal projects.

The project uses Pypi for installation.

We are open to participation on this project.
tsengine 1.0.4
python taosdb extension package

## TsEngine

This is the function package of Taos database.

### Introduction

Major TsEngine features include:
- Creating data tables using Python class objects
- Implement connection pool
- Using Python and SQL statements to operate the database

### Installing

`$ pip install tsengine`

### Example

create engine
```python
from tsengine import TsEngine

engine = TsEngine(
        host='127.0.0.1',
        user='root',
        password='',
        database='test_db'
    )
```

create session
```python

from tsengine import SessionFactory
Session = SessionFactory(engine)
```

create scope_session
```python
from tsengine import ScopeSessionFactory
Session = ScopeSessionFactory(engine)
```

create table
```python
from tsengine import Model, TimeStamp, Int, Binary

class Info(Model):
    ts = TimeStamp('ts')
    name = Binary('name', length=20)
    age = Int('age')

    class Meta:
        table_type = 'table'
        table_name = 'info'

Model.create_all(session)
```

create stable
```python
from tsengine import Model, TimeStamp, Int, Binary

class SInfo(Model):
        ts = TimeStamp('ts')
        sign = Int('sign')
        name = Binary('name', length=20)
        age = Int('age')

        class Meta:
            table_type = 'stable'
            table_name = 'sinfo'
            tags_name = 'sign, name'

Model.create_all(session)
```

create sub table
```python
from tsengine import Model

class SubInfo(Model):
    class Meta:
        table_type = 'sub_table'
        stable_name = 'sinfo'
        table_name = 'sub_info_1_cheney'
        tags_value = {'sign': 1, 'name': 'cheney'}
```

Query
```python
from tsengine import f

session.query('sinfo').select('ts, name, age').filter(f('name') == 'cheney').all()
session.query('sinfo').select('ts, name, age').filter(f('name') == 'cheney').dict()
```

Insert
```python
from datetime import date

data = dict(ts=date(2019, 10, 1), name='cheney', age=20, sign=1)
session.insert('sinfo').value(data)

data = dict(ts=date(2019, 10, 2), name='cheney')
session.insert('sinfo').column('ts, name').value(data)

data = [
    dict(ts=date(2019, 10, 3), age=20),
    dict(ts=date(2019, 10, 4), age=20),
    dict(ts=date(2019, 10, 5), age=20)
]
session.insert('sub_table').using('sinfo').tags(sign=1, name='cheney').values(data)
```
pic-diff-recognizer 1.0.0
Selenium plugin library based on image difference recognition and page intelligent exploration

# Pic-Diff-Recognizer

+ [Pic-Diff-Recognizer 中文文档](https://github.com/amazingTest/Pic-Diff-Recognizer/blob/master/README_CN.md)

Selenium plugin library based on image difference recognition and page intelligent exploration.

# installation
    
    pip install -r requirements.txt
    
    pip install pic-diff-recognizer
    
    
# best practice

    from pic_diff_recognizer.searchHandler import SearchHandler
    from violent_webdriver import Chrome
    from selenium.webdriver.chrome.options import Options
    
    
    # add some useful options :)
    chrome_options = Options()
    chrome_options.add_argument("--headless")
    chrome_options.add_argument("disable-infobars")
    chrome_options.add_experimental_option("excludeSwitches", ['enable-automation'])
    
    # init driver , executable_path should be your own path!
    dr = Chrome.violent_chromedriver(chrome_options=chrome_options,
                                     executable_path='/usr/local/bin/chromedriver')
    
    # init searchHandler
    search_handler = SearchHandler(browser=dr)
    
    # search and saving baseline images in current directory named baseline
    search_handler.traverse_href(origin_url='https://gitbook.cn/gitchat/author/5cea0bfbb78cc870612d8bba')
    
    # -------------------- assuming after some iterations of current project -----------------------------
    
    search_handler.url_histories = []
    
    # load baseline images
    search_handler.picture_handler.load_base_line()
    
    # search and comparing screen shots and baseline images
    search_handler.traverse_href(origin_url='https://gitbook.cn/gitchat/author/5cea0bfbb78cc870612d8bba',
                                 compare_baseline_and_screen_shots=True)
    
    # generate_diff_between_base_line_and_screen_shot and output diffResults to current directory
    search_handler.picture_handler.generate_diff_between_base_line_and_screen_shot()
    
    # output testReport.txt to current directory
    search_handler.picture_handler.export_picture_comparison_result()
    
    
# contact me

email address：523314409@qq.com
huobiApi 0.0.5
helper functions of huobi rest api
Requires Python: >=3.5

# HuobiApi
Huobi REST API Package(source https://github.com/MJeremy2017/HuobiApi)

__Note__: This is not an official package. For more info, please resort to official docs

## Installation
```
pip install huobiApi
```

## Get Accounts ID

```
import os
from huobiApi.service import HuobiSVC

ACCESS_KEY = os.getenv('ACCESS_KEY')
SECRET_KEY = os.getenv('SECRET_KEY')

svc = HuobiSVC(ACCESS_KEY, SECRET_KEY, url_type='normal')  # or aws

svc.get_accounts()
```
---
```
{'status': 'ok',
 'data': [{'id': 01, 'type': 'spot', 'subtype': '', 'state': 'working'},
  {'id': 02, 'type': 'margin', 'subtype': 'btcusdt', 'state': 'working'},
  {'id': 03, 'type': 'margin', 'subtype': 'eosusdt', 'state': 'working'},
  {'id': 04, 'type': 'margin', 'subtype': 'ethusdt', 'state': 'working'},
  {'id': 05, 'type': 'margin', 'subtype': 'neousdt', 'state': 'working'},
  {'id': 06, 'type': 'otc', 'subtype': '', 'state': 'working'},
  {'id': 07, 'type': 'super-margin', 'subtype': '', 'state': 'working'}]}

```

## Get Kline Data
```
symbol = 'btcusdt'
res = svc.get_kline(symbol, '60min', size=50)
```
---
```
{'status': 'ok',
 'ch': 'market.btcusdt.kline.60min',
 'ts': 1580378774791,
 'data': [{'amount': 66.60260811521935,
   'open': 9364.89,
   'close': 9366.58,
   'high': 9376.21,
   'id': 1580378400,
   'count': 1080,
   'low': 9364.89,
   'vol': 624201.8357696668},
   ...
```

## Place an Order
```
data = svc.send_order(
                acct_id='01',
                amount='0.001',
                price='7999',
                source='api',
                symbol='btcusdt',
                _type='sell-stop-limit',
                stop_price='8000',
                operator='lte')

```