semvec/pypi-packages huggingface dataset:
LocalDataStore 1.5.1
A File Based DataStore
License: MIT
Requires Python: >=3.6

Built a file-Based Key-Value DataStore that supports the basic CRD(Create,read and delete) operations . 
This data store is meant to be used as a local storage for one single process on one laptop. The data store is exposed as a library
to the clients that can instantiate a class and work with the data store.

The data store will support the following functional requirements

1. It can be initialized using an optional file path. if one is not provided, it will reliably create itself in a resonable location on the laptop

2. A New Key Value pair can be added to the data store using the create operation. The key is always a string- capped at 32 chars. the value is always a JSON object - capped at 16KB

3. If Create is invoked from an existing key, an appropriate error must be returned.

4. A Read operation on a key can be performed by providing a key, and recieving the value in response as a JSON object 

5. A Delete operation can be performed by providing a key

6. Every Key supports setting a TIME TO LIVE property when it is created. This property is optional. if provided it will be evaluated as an integer defining the number of seconds 
   the key must be retained in the data store Once the TIME TO LIVE for a key has epired, the key will no longer be available for read or delete operation

7. Appropriate error messages must always be returned to a client if it uses the data store in unexpected ways or breached any limits


The data Store will also support the following non functional requirements 

1. The size of the file storing the data must never exceed 1GB

2. More than on Client process cannot be allowed to use the same file as a data store at any given time.

3. A client process is allowed to accedd the data store using multiple threads (if it desires to )
   the data must therefore be THREAD-SAFE

4. The client will bear as little memory costs as possible to use this data store while deriving maximum performance with respect to response times for accessing the data store
phishing-detection-engine 0.0.17
Library for Detecting Phishing URLs
License: MIT

The project is using different techniques to identify phishing URLs.
               Machine Learning and use of different APIs is done to get good results.
               At first, model checks the URL in databases of phishing URLs. 
               If URL is found in database, user is given output immediaately.
               If URL is not categorized at that point, then it is categorized using
               machine learning model whcih is trained on dataset of above 18000 Websites
pythonFTP 0.1.0
FTP file transfer and management by Python
License: MIT
Requires Python: >=3.6

# pythonFTP
## 地址

 - Code [github](https://github.com/AsajuHuishi/FTP_file_transfer_management/tree/main/pyFTP)
 - [Pypi: pythonFTP](https://pypi.org/project/pythonFTP/)

## 介绍
`pythonFTP` 是一个用来在Linux（Ubuntu）上管理ftp服务器文件的工具。它使用`python`实现，基于经典的`libftp`模块，保留了该模块的所有原有功能。它实现的核心功能包括：**ftp服务器上传/下载文件/文件夹，在ftp服务器上创建文件夹，删除ftp服务器上的文件/文件夹**。我们**对ftp的文件夹实现递归处理**，确保可以**实现便利的传输和管理ftp服务器上的文件和文件夹**。

## 环境

 - Ubuntu16.04
 - Python3.7
 - [Serv-U](http://www.serv-u.com.cn/)

##  下载

```bash
pip install pythonFTP
```
## 使用

 - **模块导入**
```python
from pythonFTP.FTPTools import FTPTools
```
 - **对象建立**
 

```python
obj = FTPTools('ip', 'username', 'password')
```
- **核心功能实现**

| run() |  参数1     | 参数2|参数3|
|:--------:|:-------------:|:--------:|:--------:|
| **上传文件夹** |  ftp文件夹路径 |本地文件夹路径 |`'upload folder'`|
| **上传文件** | ftp文件夹路径 | 本地文件+文件名 |`'upload file'`|
| **下载文件夹** |  ftp文件夹路径 |本地文件夹路径 |`'download folder'`|
| **下载文件** | ftp文件路径+文件名 |本地文件夹路径 | `'download file'`|
| **删除文件夹** |  ftp文件夹路径 |`''` |`'delete folder'`|
| **删除文件** |  ftp文件路径+文件名 |`''` |`'delete file'`|
| **创建文件夹**| ftp文件夹路径|`''` |`'create folder'`|

**举例**

```python
localPath = '/media/lwt/qysdcj/'
ftpPath = '/private/lwt/qysdcj/'
obj.run(ftpPath, localPath, 'upload folder')

# 上传一个文件
localFile = '/media/lwt/qysdcj/GT_136.tif'
ftpPath = '/private/lwt/qysdcj/'
obj.run(ftpPath, localFile, 'upload file')

# 删除文件
i = 136
ftpFile = '/private/lwt/qysdcj/GT_'+str(i)+'.tif'
obj.run(ftpFile, '', 'delete file')

# 删除文件夹
ftpFolder = '/private/lwt/qysdcj/'
obj.run(ftpFolder, '', 'delete folder')    

# 下载文件
ftpFile = '/private/lwt/qysdcj/LR_1.tif'
localPath = '/media/lwt/qysdcj/01trainset/'
obj.run(ftpFile, localPath, 'download file')    

# 下载文件夹
ftpPath = '/private/lwt/qysdcj/'
localPath = '/media/lwt/qysdcj/01trainset/'
obj.run(ftpPath, localPath, 'download folder')    

# 创建文件夹
ftpPath = '/private/zengxinyang/qysdcj/'
obj.run(ftpPath, '', 'create folder') 
```

## 相关项目

 - [libftp](https://pypi.org/search/?q=libftp) 本项目在此项目的基础上进行了修改，并保留了原有的所有方法。您可以在`pyFTP`中使用以下命令，它包括原来模块中的所有功能。

```python
from pythonFTP.ftplib2 import FTP 
```


## 负责人

 - [AsajuHuishi](https://github.com/AsajuHuishi)
Geospark-test 0.0.4
Listen to location updates.
License: MIT
Requires Python: >=3.5

QuickStart Guide

pip install Geospark-python-sdk

from geospark import Client
# For project level
client = Client(API_KEY=<API-KEY>)

# For user level
client = Client(API_KEY=<API-KEY>, USER_ID=<USER-ID>)

# To start listening to locations
client.sub()

# To stop listening to locations
client.disconnect()

By default the SDK prints out the locations. If the locations are required to any other output, then
please use a callback function like the example below-

def custom_callback_function(client, userdata, msg):
    # print("")
    # save to file
    # log etc

client = Client(API_KEY=<API-KEY>, CALLBACK=<custom_callback_function>)