semvec/pypi-packages huggingface dataset:
rate-limit 0.0.5
distributed rate limiter
Keywords: rate,rate-limit,limit,redis-cell

# rate-limit
### 安装方式
pip install rate-limit

### 使用说明
基于redis-cell扩展的限流，使用该包需要安装redis-cell扩展，支持分布式限流。

目前只支持异步方法的限流，使用方式如下：
``` 
from ratelimit.decorators import rate_limit

# 这里的key_name必须要在一个服务中唯一，不然会有冲突
@rate_limit("key_name")
def need_limit_method():
    ...
```

### 修改配置
```
from ratelimit.base.constants import RedisConfig, LimitConfig

# 这里是redis连接信息
RedisConfig.host = '127.0.0.1'
RedisConfig.port = 6379
RedisConfig.passwors = ''
RedisConfig.db = 0

# 这里是默认的限流配置
LimitConfig.service = 'default'         # 限流器所属服务
LimitConfig.total_quota = 100           # 总令牌桶数量
LimitConfig.quota = 3                   # 单位时间内生成的令牌数
LimitConfig.limit_second = 1            # 单位时间
LimitConfig.once_quota = 1              # 一次请求获取的令牌数
LimitConfig.default_handle = 'discard'  # 被限流时的处理方式，默认丢弃【discard丢弃；queue排队；retry重试】
```

### 配置写在redis中
```
在redis中可以根据实际情况配置限流信息，格式如下：
    "service": {
        "key_name": {
            "total_quota": 100,          # 令牌桶大小
            "limit_second": 10,          # 生成令牌的单位时间
            "limit_quota": 3,            # 单位时间内生成的令牌数量
            "once_quota": 1,             # 每次请求消费的令牌数量
            "handle": "discard",         # discard丢弃；queue排队；retry重试
            "handle_params": {},         # 处理方式对应的参数
        }
    }
这里的key_name要对应装饰器的key_name

handle_params的配置如下：
1、handle 为 discard 类型的，无需配置
2、handle 为 queue 类型的，配置如下：
    {
        "delay": 3,               # 延时执行时间，单位【秒】
        "limit_delay": 1,         # 执行再次被限制的情况下，延迟执行时间，单位【秒】
        "queue_type": "redis",    # 队列类型：redis【基于redis队列】、local【基于本地内存队列】
    }
3、handle 为 retry 类型的，配置如下：
    {
        "retry_count": 3,    # 重试次数
        "retry_wait": 0,     # 每次重试间隔，默认不等待，单位【秒】
        "current_count": 0,  # 当前已重试几次
    }
```
Explain-LISA-CNN-test-4 0.0.1
Unified Explanation Provider For CNNs
Keywords: LIME,Integrated gradients,SHAP,Anchors,Explainable AI,XAI,CNN Explainer


# Explain LISA
It takes the following.
img: local path of img to be explained
class_names: the classes available as predictions for the given model
img_shape: shape of the image accepts by the neural network
model: the model to be explained get from tf.keras.models.load_model("your model path")
img1: local path background data point for produce explanations with SHAP
img2: local path background data point for produce explanations with SHAP
scale: for manual image scaling if scaling layer absent in the model to be explained 
filter_radius: the pixel value of the radius of the High pass filter

## Installation
```pip install Explain_LISA_CNN_Prediction```

## How to use it?
Open terminal and type python/python3 according to your OS.


``` import Explain_LISA_CNN_01 as e```
``` e.ExplainLISA(img,class_names,img_shape,model,img1,img2,scale,filter_radius)```

## License

© 2021 Sudil H.P Abeyagunasekera

This repository is licensed under the MIT license. See LICENSE for details.
efficient-test 1.0.5
testdata include chinese personal four element and offen use datetime 测试数据包含随机生成的中国公民四要素，及常用的日期时间｜通过身份证号获得性别、生日、年龄，识别真伪｜根据swagger文档生成规则用例
Requires Python: >=3.6

# efficient-test

## testdata include chinese personal four element and offen use datetime 

测试数据包含随机生成的中国公民四要素，及常用的日期时间

## shell命令执行方法封装，以及常用的文件处理方法

## swagger2case
通过读取swagger文档，生成规则的测试用例，如-全参数，不传，传空。仅必填项和必填项逐个校验占未实现，敬请期待。

## jmeter
规范性能测试项目，实现无人值守执行多场景
spark-gaps-date-rorct-tools 0.0.1
spark_gaps_date_rorct_tools
Keywords: spark,gaps,date

# spark_gaps_date_rorc_tools


[![Github License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
[![Updates](https://pyup.io/repos/github/woctezuma/google-colab-transfer/shield.svg)](pyup)
[![Python 3](https://pyup.io/repos/github/woctezuma/google-colab-transfer/python-3-shield.svg)](pyup)
[![Code coverage](https://codecov.io/gh/woctezuma/google-colab-transfer/branch/master/graph/badge.svg)](codecov)




spark_gaps_date_rorc_tools is a Python library that implements get gaps dates
## Installation

The code is packaged for PyPI, so that the installation consists in running:
```sh
pip install spark-gaps-date-rorc-tools 
```


## Usage

wrapper take gaps dates



## License

[Apache License 2.0](https://www.dropbox.com/s/8t6xtgk06o3ij61/LICENSE?dl=0).


## New features v1.0

 
## BugFix
- choco install visualcpp-build-tools



## Reference

 - Jonathan Quiza [github](https://github.com/jonaqp).
 - Jonathan Quiza [RumiMLSpark](http://rumi-ml.herokuapp.com/).
 - Jonathan Quiza [linkedin](https://www.linkedin.com/in/jonaqp/).
ngtr4 2.0.12
dgfs
Requires Python: >=3.6, <4
Keywords: sample,setuptools,development

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pygst 0.0.4
Python global stock time
Requires Python: >=3.6

# pygst (Python global stock time)

This lib will tell you what is current market status of your stock.

Holiday is coming soon.

## Example

```
from pygst import get_market_status, MarketStatus

status = get_market_status("AAPL")
if status == MarketStatus.PRE or status == MarketStatus.POST:
    print("Extended time")
else:
    print(f"{status.name.lower()} time")

```