semvec/pypi-packages huggingface dataset:
pandas-gbq-magic 1.1.2
The package provides as magic on top of Pandas GBQ to make querying in Jupter envioronment easy and user  friendly
Requires Python: >=3.6


# Big-Query-Magic

#### The package has been created for Mac OS
#### Requirements
It is assumed that you have basic packages like pandas installed
Install Auth2client and pandas_gbq
Ensure that you can query data using pandas gbq
<hr>

This packacge installs a magic in your startup directory which makes querying in jupyter environment more user friendly and easier to use.Post intallation simply type %%BQSQL and write your query
example
```python
%%BQSQL
SELECT *
FROM table
LIMIT 10;
```

<b>There are other features also present which makes it even more user friendly which can be explained with help of the argument this magic can take</b>

-job [Y or None] If Y is passed as job argument this will run just the query but will not pull the out put, this is useful when one is creating a large temp table during the workflow and does not want to download and load it in python, the existing pandas_gbq does not offer that

-save_to [Table Name] Pass a variable in which the output needs to be store

Note Do not pass both the arguments at the same time

-para [Y or None] If Y is passed the query will look if parameters or python variables are used in the query. Yes this is one of the best features of this magic you can use python variables directly in your query

example
```python
x = ['user1','user2']```

```python
%%BQSQL -para Y -job Y
SELECT *
FROM table
WHERE user_id IN @x
```
Currently string int and list of these two can be passed as a parameter. Note parameter needs to be preceded by <b><u> @ </u></b> in case one was planning to use @ just as character in that case please avoid using parameter

#### Installation
Run
```python
from pandas_gbq_magic import magic
magic.install('You Bigquery Project name')
```
Restart Jupyter notebook
the-money-converter 1.0.1
货币汇率转换
Requires Python: >=3.0

# The Money Converter

Python汇率转换工具类，数据来源于[themoneyconverter](https://themoneyconverter.com/zh-CN)

## 快速入门
安装
```shell
pip install themoneyconverter
```

使用

```python
from themoneyconverter import MoneyConverter, Currency


if __name__ == '__main__':
    # 获取1元人民币转换其它货币的汇率
    moneyConverter = MoneyConverter(Currency.CNY.name)
    moneyConverter.refresh()
    rate = moneyConverter.get_rate(Currency.ARS.name)
    print(Currency.ARS.value, rate)
```

执行结果示例
```python
Connected to pydev debugger (build 203.7717.81)
阿根廷比索 30.9827

Process finished with exit code 0
```

代码说明
```python
class MoneyConverter:
    URL_TEMPLATE = 'https://themoneyconverter.com/zh-CN/{source}/{target}?amount=1.00'

    def __init__(self, source='CNY', target='CNY'):
        self.rate = {}
        self.source = source
        self.target = target
        self.updateTime = None
```
source是转出货币，target是转入货币，比如说`moneyConverter = MoneyConverter(Currency.CNY.name)`是1元人民币转换其它货币的汇率，target用默认值即可，目前没什么用

支持以下货币汇率互相转换
+ AED = 阿联酋迪拉姆
+ JPY = 日元
+ ARS = 阿根廷比索
+ KRW = 韩元
+ AUD = 澳元
+ MAD = 摩洛哥迪拉姆
+ BRL = 巴西雷亚尔
+ MXN = 墨西哥比索
+ CAD = 加元
+ NOK = 挪威克朗
+ CHF = 瑞士法郎
+ NZD = 新西兰元
+ CNY = 人民币
+ PHP = 菲律宾比索
+ CZK = 捷克克朗
+ PLN = 波兰兹罗提
+ DKK = 丹麦克朗
+ RUB = 俄罗斯卢布
+ EUR = 欧元
+ SEK = 瑞典克朗
+ GBP = 英镑
+ SGD = 新加坡元
+ HKD = 港元
+ THB = 泰铢
+ HUF = 匈牙利福林
+ TRY = 土耳其里拉
+ ILS = 以色列谢克尔
+ USD = 美元
+ INR = 印度卢比
+ ZAR = 南非南特
cxlint 1.0.4
A static code analyzer that provides automated quality       control for Dialogflow CX Agents
Requires Python: >=3.6, <4
Keywords: dialogflow,cx,google,bot,chatbot,linter,dfcx

# Dialogflow CX Linter
<a href="https://github.com/googleapis/google-cloud-python/blob/main/README.rst#stability-levels" alt="preview">
<img src="https://img.shields.io/badge/support-stable-gold" /></a>
<a href="https://pypi.org/project/cxlint/" alt="preview">
<img src="https://img.shields.io/badge/python-3.8%20%7C%203.9%20%7C%203.10-blue" /></a>

\
Similar to [code linting](https://en.wikipedia.org/wiki/Lint_(software)), Dialogflow CX Agents can benefit from an automated linter to catch various common design defects when developing Agents.
The primary goal is to minimize common defects shipped to production by proactively catching and fixing them.


# Quick Start

In order to use this library, you first need to go through the following steps:

1. Select or create a [Cloud Platform](https://console.cloud.google.com/project) project.
2. [Enable billing](https://cloud.google.com/billing/docs/how-to/modify-project#enable_billing_for_a_project) for your project.
3. [Setup Authentication.](https://googleapis.dev/python/google-api-core/latest/auth.html)

## Mac/Linux
``` bash
pip install virtualenv
virtualenv <your-env>
source <your-env>/bin/activate
<your-env>/bin/pip install google-cloud-dialogflow-cx
```

## Windows
-------

```bash
pip install virtualenv
virtualenv <your-env>
<your-env>\Scripts\activate
<your-env>\Scripts\pip.exe install google-cloud-dialogflow-cx
```

# Authentication
Authentication can vary depending on how and where you are interacting with Dialogfow CX Linter.

## Google Colab
If you're using cxlint with a [Google Colab](https://colab.research.google.com/) notebook, you can add the following to the top of your notebook for easy authentication

``` python
project_id = '<YOUR_GCP_PROJECT_ID>'

# this will launch an interactive prompt that allows you to auth with GCP in a browser
!gcloud auth application-default login --no-launch-browser

# this will set your active project to the `project_id` above
!gcloud auth application-default set-quota-project $project_id
```

After running the above, Colab will pick up your credentials from the environment. No need to use Service Account keys!

# Rules

Curent [list of rules](docs/RULES.md) that are being implemented for CX Linter.<br>
If you have an idea for a new rule, please submit a Feature Request!

# Examples

Code samples and snippets live in the [examples/](examples) folder.

# Supported Python Versions
Python >= 3.8

# Contributing
We welcome any contributions or feature requests you would like to submit!

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License
=======
Distributed under the Apache 2.0 License. See [LICENSE](../LICENSE.txt) for more information.

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